{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}/Users/adamenders/Dropbox/Perceived vs. Affective Polarization/Data and Code/Supplemental Analysis, Stata log.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res} 9 Mar 2020, 13:43:45

{com}. use "/Users/adamenders/Dropbox/Perceived vs. Affective Polarization/Data and Code/Cumulative/anes_timeseries_cdf.dta"

. do "/var/folders/xb/ddtsf7g93xd57f7hhtnm9lyc0000gp/T//SD59652.000000"
{txt}
{com}. ********************************************************************************
. ********************************************************************************
. ********************************************************************************
. ********************************************************************************
. 
. ****
. ** Open ANES Cumulative File
. ****
. 
. set more off
{txt}
{com}. 
. * use "anes_timeseries_cdf.dta"
. 
. ********************************************************************************
. 
. ****
. ** Data cleaning and recoding
. ****
. 
. * Create ID and year identifiers
. gen caseid = VCF0006
{txt}
{com}. gen year = VCF0004
{txt}
{com}. gen sample = 1
{txt}
{com}. 
. 
. * Survey weights
. gen weight = VCF0009x
{txt}
{com}. 
. 
. * Survey mode
. gen svymode = VCF0017
{txt}
{com}. drop if svymode == 4
{txt}(6,950 observations deleted)

{com}.         
.         
. * Self ideology (recoded to range -3-3; -2 Havent thought, -8 DK, -9 NA)
. gen ideo = VCF0803
{txt}(15,316 missing values generated)

{com}. replace ideo = . if ideo < 1 
{txt}(1,846 real changes made, 1,846 to missing)

{com}. replace ideo = . if ideo == 9 
{txt}(9,775 real changes made, 9,775 to missing)

{com}. recode ideo (1=-3) (2=-2) (3=-1) (4=0) (5=1) (6=2) (7=3)
{txt}(ideo: 26057 changes made)

{com}. 
. gen conserv = 1 if ideo > 0 & ideo < 4
{txt}(42,437 missing values generated)

{com}. replace conserv = 0 if ideo < 0
{txt}(6,745 real changes made)

{com}. 
. 
. * Strength of ideological predisposition
. gen ideostrength = 0 if ideo == 0
{txt}(44,239 missing values generated)

{com}. replace ideostrength = 1 if ideo == -1
{txt}(3,253 real changes made)

{com}. replace ideostrength = 1 if ideo == 1
{txt}(4,881 real changes made)

{com}. replace ideostrength = 2 if ideo == -2
{txt}(2,832 real changes made)

{com}. replace ideostrength = 2 if ideo == 2
{txt}(4,798 real changes made)

{com}. replace ideostrength = 3 if ideo == -3
{txt}(660 real changes made)

{com}. replace ideostrength = 3 if ideo == -3
{txt}(0 real changes made)

{com}. 
. 
. * Self party ID (recoded to range -3-3; -2 DK NA)
. gen pid = VCF0301 
{txt}(662 missing values generated)

{com}. replace pid = . if pid == 0
{txt}(1,003 real changes made, 1,003 to missing)

{com}. recode pid (1=-3) (2=-2) (3=-1) (4=0) (5=1) (6=2) (7=3)
{txt}(pid: 51329 changes made)

{com}. 
. gen rep = 1 if pid > 0 & pid < 4
{txt}(34,760 missing values generated)

{com}. replace rep = 0 if pid < 0
{txt}(27,141 real changes made)

{com}. 
. 
. * Strength of ideological predisposition
. gen pidstrength = 0 if pid == 0
{txt}(47,040 missing values generated)

{com}. replace pidstrength = 1 if pid == -1
{txt}(6,175 real changes made)

{com}. replace pidstrength = 1 if pid == 1
{txt}(5,201 real changes made)

{com}. replace pidstrength = 2 if pid == -2
{txt}(10,833 real changes made)

{com}. replace pidstrength = 2 if pid == 2
{txt}(7,077 real changes made)

{com}. replace pidstrength = 3 if pid == -3
{txt}(10,133 real changes made)

{com}. replace pidstrength = 3 if pid == -3
{txt}(0 real changes made)

{com}. 
. 
. * Education (ranges from 1-7)
. gen edu = VCF0140a
{txt}(662 missing values generated)

{com}. replace edu = . if edu >= 8
{txt}(502 real changes made, 502 to missing)

{com}. label define edulab 1 "8 grades or less" 2 "9-12 grades" 3 "High school" ///
>         4 "HS + non-academic training" 5 "Some college" 6 "BA" 7 "Advanced"
{txt}
{com}. label values edu edulab
{txt}
{com}. 
. 
. * Race 
. gen race = VCF0105a
{txt}(1,139 missing values generated)

{com}. replace race = . if race == 9
{txt}(352 real changes made, 352 to missing)

{com}. 
. gen black = 1 if race == 2
{txt}(46,879 missing values generated)

{com}. replace black = 0 if race != 2 & race != .
{txt}(45,388 real changes made)

{com}. 
. gen hispanic = 1 if race == 5
{txt}(49,868 missing values generated)

{com}. replace hispanic = 0 if race != 5 & race != .
{txt}(48,377 real changes made)

{com}. 
. 
. * Gender (1=female)
. gen gender = VCF0104
{txt}
{com}. replace gender = . if gender < 1
{txt}(122 real changes made, 122 to missing)

{com}. gen female = 1 if gender == 2
{txt}(23,577 missing values generated)

{com}. recode female (.=0)
{txt}(female: 23577 changes made)

{com}. label define genderlab 0 "Male" 1 "Female"
{txt}
{com}. label values female genderlab
{txt}
{com}. 
. 
. * Age (number of years) 
. gen age = VCF0101
{txt}(1,801 missing values generated)

{com}. replace age = . if age == 00
{txt}(442 real changes made, 442 to missing)

{com}. 
. 
. * Region
. gen south = .
{txt}(52,994 missing values generated)

{com}. replace south = 0 if VCF0112 == 1
{txt}(10,096 real changes made)

{com}. replace south = 0 if VCF0112 == 2
{txt}(13,820 real changes made)

{com}. replace south = 0 if VCF0112 == 4
{txt}(9,338 real changes made)

{com}. replace south = 1 if VCF0112 == 3
{txt}(17,939 real changes made)

{com}. label var south "South Region Dummy"
{txt}
{com}. label define southern 0 "0 Non-South" 1 "1 South"
{txt}
{com}. label values south southern
{txt}
{com}. 
. 
. * Income
. gen income = VCF0114 - 1
{txt}(1,511 missing values generated)

{com}. replace income = . if income < 0
{txt}(3,749 real changes made, 3,749 to missing)

{com}. 
. 
. * Religiosity
. gen religiosity = VCF0130
{txt}(13,809 missing values generated)

{com}. recode religiosity (0=.) (7=.) (8=.) (9=.) (5=0) (4=1) (3=2) (2=3) (1=4)
{txt}(religiosity: 39185 changes made)

{com}. 
.  
. * Number of party likes/dislikes (0 - 5 likes)
. gen demlike = VCF0314
{txt}(15,819 missing values generated)

{com}. replace demlike = . if demlike == 9
{txt}(4,419 real changes made, 4,419 to missing)

{com}. 
. gen demdislike = VCF0315
{txt}(15,819 missing values generated)

{com}. replace demdislike = . if demdislike == 9
{txt}(4,419 real changes made, 4,419 to missing)

{com}. 
. gen replike = VCF0318
{txt}(15,819 missing values generated)

{com}. replace replike = . if replike == 9
{txt}(4,419 real changes made, 4,419 to missing)

{com}. 
. gen repdislike = VCF0319
{txt}(15,819 missing values generated)

{com}. replace repdislike = . if repdislike == 9
{txt}(4,419 real changes made, 4,419 to missing)

{com}. 
. 
. * Feeling thermometers
. gen liberaltherm = VCF0211
{txt}(11,694 missing values generated)

{com}. replace liberaltherm = . if liberaltherm >= 98
{txt}(6,313 real changes made, 6,313 to missing)

{com}. gen conservtherm = VCF0212
{txt}(11,694 missing values generated)

{com}. replace conservtherm = . if conservtherm >= 98
{txt}(6,121 real changes made, 6,121 to missing)

{com}. gen ideothermdiff = abs(liberaltherm - conservtherm)
{txt}(18,698 missing values generated)

{com}. 
. 
. gen dempartytherm = VCF0218
{txt}(23,355 missing values generated)

{com}. replace dempartytherm = . if dempartytherm >= 98
{txt}(1,311 real changes made, 1,311 to missing)

{com}. gen reppartytherm = VCF0224
{txt}(23,355 missing values generated)

{com}. replace reppartytherm = . if reppartytherm >= 98
{txt}(1,346 real changes made, 1,346 to missing)

{com}. gen partydifftherm = abs(dempartytherm - reppartytherm)
{txt}(24,821 missing values generated)

{com}. 
. 
. gen demcandtherm = VCF0424
{txt}(27,799 missing values generated)

{com}. replace demcandtherm = . if demcandtherm >= 98
{txt}(891 real changes made, 891 to missing)

{com}. gen repcandtherm = VCF0426
{txt}(27,799 missing values generated)

{com}. replace repcandtherm = . if repcandtherm >= 98
{txt}(806 real changes made, 806 to missing)

{com}. gen diffcandtherm = abs(demcandtherm - repcandtherm)
{txt}(28,868 missing values generated)

{com}. 
. 
. * Affective polarization
. alpha ideothermdiff partydifftherm diffcandtherm, gen(affectpol)

{txt}Test scale = mean(unstandardized items)

Average interitem covariance:{col 34}{res} 280.6224
{txt}Number of items in the scale:{col 34}{res}        3
{txt}Scale reliability coefficient:{col 34}{res}   0.6872
{txt}
{com}. 
. 
. * Party placement on ideological scale
. gen demideo = VCF0503
{txt}(16,827 missing values generated)

{com}. replace demideo = . if demideo == 0
{txt}(5,746 real changes made, 5,746 to missing)

{com}. replace demideo = . if demideo == 8
{txt}(3,109 real changes made, 3,109 to missing)

{com}. 
. gen repideo = VCF0504
{txt}(16,827 missing values generated)

{com}. replace repideo = . if repideo == 0
{txt}(5,754 real changes made, 5,754 to missing)

{com}. replace repideo = . if repideo == 8
{txt}(3,237 real changes made, 3,237 to missing)

{com}. 
. gen partyideodiff = abs(demideo - repideo)
{txt}(26,078 missing values generated)

{com}. 
. 
. * Candidate placement on ideological scale
. gen dcandideo = VCF9088
{txt}(29,356 missing values generated)

{com}. replace dcandideo = . if dcandideo == 0
{txt}(2,272 real changes made, 2,272 to missing)

{com}. replace dcandideo = . if dcandideo >= 8
{txt}(3,712 real changes made, 3,712 to missing)

{com}. 
. gen rcandideo = VCF9089
{txt}(36,363 missing values generated)

{com}. replace rcandideo = . if rcandideo == 0
{txt}(1,183 real changes made, 1,183 to missing)

{com}. replace rcandideo = . if rcandideo >= 8
{txt}(3,334 real changes made, 3,334 to missing)

{com}. 
. gen candideodiff = abs(dcandideo - rcandideo)
{txt}(42,584 missing values generated)

{com}. 
. 
. * Sorting
. gen sorting = abs(ideo - (-1*pid)) * (ideostrength * pidstrength)
{txt}(31,099 missing values generated)

{com}. 
. 
. * Placement on guaranteed jobs scale 
. gen selfjobs = VCF0809
{txt}(16,827 missing values generated)

{com}. replace selfjobs = . if selfjobs == 0
{txt}(3,675 real changes made, 3,675 to missing)

{com}. replace selfjobs = . if selfjobs >= 8
{txt}(4,292 real changes made, 4,292 to missing)

{com}. label values selfjobs jobslab
{txt}
{com}. 
. gen demjobs = VCF0513
{txt}(27,480 missing values generated)

{com}. replace demjobs = . if demjobs == 0
{txt}(1,652 real changes made, 1,652 to missing)

{com}. replace demjobs = . if demjobs >= 8
{txt}(6,162 real changes made, 6,162 to missing)

{com}. label values demjobs jobslab
{txt}
{com}. 
. gen repjobs = VCF0514
{txt}(27,480 missing values generated)

{com}. replace repjobs = . if repjobs == 0
{txt}(1,661 real changes made, 1,661 to missing)

{com}. replace repjobs = . if repjobs >= 8
{txt}(6,181 real changes made, 6,181 to missing)

{com}. label values repjobs jobslab
{txt}
{com}. 
. gen pdiffjobs = abs(demjobs - repjobs)
{txt}(35,594 missing values generated)

{com}. 
. 
. * Self placement on aid to blacks scale 
. gen selfaid = VCF0830
{txt}(15,320 missing values generated)

{com}. replace selfaid = . if selfaid == 0
{txt}(1,802 real changes made, 1,802 to missing)

{com}. replace selfaid = . if selfaid >= 8
{txt}(4,143 real changes made, 4,143 to missing)

{com}. label values selfaid aidlab
{txt}
{com}. 
. 
. * Party placement on aid to blacks scale 
. gen demaid = VCF0517
{txt}(28,532 missing values generated)

{com}. replace demaid = . if demaid == 0
{txt}(1,841 real changes made, 1,841 to missing)

{com}. replace demaid = . if demaid >= 8
{txt}(5,969 real changes made, 5,969 to missing)

{com}. label values demaid aidlab
{txt}
{com}. 
. gen repaid = VCF0518
{txt}(28,532 missing values generated)

{com}. replace repaid = . if repaid == 0
{txt}(1,850 real changes made, 1,850 to missing)

{com}. replace repaid = . if repaid >= 8
{txt}(6,095 real changes made, 6,095 to missing)

{com}. label values repaid aidlab
{txt}
{com}. 
. gen pdiffaid = abs(demaid - repaid)
{txt}(36,691 missing values generated)

{com}. 
. 
. * Self placement on government services scale 
. gen selfservice = VCF0839
{txt}(27,273 missing values generated)

{com}. replace selfservice = . if selfservice == 0
{txt}(2,081 real changes made, 2,081 to missing)

{com}. replace selfservice = . if selfservice >= 8
{txt}(3,601 real changes made, 3,601 to missing)

{com}. recode selfservice (1=7) (2=6) (3=5) (4=4) (5=3) (6=2) (7=1)
{txt}(selfservice: 14301 changes made)

{com}. 
. 
. * Party placement on government services scale 
. gen demservice = VCF0541
{txt}(30,775 missing values generated)

{com}. replace demservice = . if demservice == 0
{txt}(2,558 real changes made, 2,558 to missing)

{com}. replace demservice = . if demservice >= 8
{txt}(2,553 real changes made, 2,553 to missing)

{com}. recode demservice (1=7) (2=6) (3=5) (4=4) (5=3) (6=2) (7=1)
{txt}(demservice: 13723 changes made)

{com}. 
. gen repservice = VCF0542
{txt}(30,775 missing values generated)

{com}. replace repservice = . if repservice == 0
{txt}(2,574 real changes made, 2,574 to missing)

{com}. replace repservice = . if repservice >= 8
{txt}(2,531 real changes made, 2,531 to missing)

{com}. recode repservice (1=7) (2=6) (3=5) (4=4) (5=3) (6=2) (7=1)
{txt}(repservice: 13323 changes made)

{com}. 
. gen pdiffservice = abs(demservice - repservice)
{txt}(36,093 missing values generated)

{com}. 
. 
. * Self placement on defense spending scale 
. gen selfdefense = VCF0843
{txt}(28,994 missing values generated)

{com}. replace selfdefense = . if selfdefense == 0
{txt}(2,091 real changes made, 2,091 to missing)

{com}. replace selfdefense = . if selfdefense >= 8
{txt}(2,943 real changes made, 2,943 to missing)

{com}. 
. 
. * Party placement on defense spending scale 
. gen demdefense = VCF0549
{txt}(34,291 missing values generated)

{com}. replace demdefense = . if demdefense == 0
{txt}(2,427 real changes made, 2,427 to missing)

{com}. replace demdefense = . if demdefense >= 8
{txt}(2,548 real changes made, 2,548 to missing)

{com}. 
. gen repdefense = VCF0550
{txt}(34,291 missing values generated)

{com}. replace repdefense = . if repdefense == 0
{txt}(2,433 real changes made, 2,433 to missing)

{com}. replace repdefense = . if repdefense >= 8
{txt}(2,346 real changes made, 2,346 to missing)

{com}. 
. gen pdiffdefense = abs(demdefense - repdefense)
{txt}(39,450 missing values generated)

{com}. 
. 
. * Self placement on government health insurance scale
. gen selfinsure = VCF0806
{txt}(25,364 missing values generated)

{com}. replace selfinsure = . if selfinsure == 0
{txt}(4,718 real changes made, 4,718 to missing)

{com}. replace selfinsure = . if selfinsure == 9
{txt}(3,018 real changes made, 3,018 to missing)

{com}. 
. 
. * Party placement on government health insurance scale
. gen deminsure = VCF0508
{txt}(38,341 missing values generated)

{com}. replace deminsure = . if deminsure == 0
{txt}(3,236 real changes made, 3,236 to missing)

{com}. replace deminsure = . if deminsure >= 8
{txt}(2,485 real changes made, 2,485 to missing)

{com}. 
. gen repinsure = VCF0509
{txt}(38,341 missing values generated)

{com}. replace repinsure = . if repinsure == 0
{txt}(3,241 real changes made, 3,241 to missing)

{com}. replace repinsure = . if repinsure >= 8
{txt}(2,622 real changes made, 2,622 to missing)

{com}. 
. gen pdiffinsure = abs(deminsure - repinsure)
{txt}(44,347 missing values generated)

{com}. 
. 
. * Perceived polarization
. alpha pdiffinsure pdiffdefense pdiffservice pdiffaid ///
>         pdiffjobs partyideodiff, gen(perceivepol)

{txt}Test scale = mean(unstandardized items)

Average interitem covariance:{col 34}{res} 1.368159
{txt}Number of items in the scale:{col 34}{res}        6
{txt}Scale reliability coefficient:{col 34}{res}   0.8589
{txt}
{com}. 
.         
. * Issue extremity
. gen issex1 = abs(selfdefense - 4)
{txt}(34,028 missing values generated)

{com}. gen issex2 = abs(selfservice - 4)       
{txt}(32,955 missing values generated)

{com}. gen issex3 = abs(selfaid - 4)   
{txt}(21,265 missing values generated)

{com}. gen issex4 = abs(selfinsure - 4)        
{txt}(33,100 missing values generated)

{com}. gen issex5 = abs(selfjobs - 4)  
{txt}(24,794 missing values generated)

{com}.         
. alpha issex1-issex5, gen(issextreme)    

{txt}Test scale = mean(unstandardized items)

Average interitem covariance:{col 34}{res} .3001629
{txt}Number of items in the scale:{col 34}{res}        5
{txt}Scale reliability coefficient:{col 34}{res}   0.6191
{txt}
{com}.         
. 
. * Self placement on abortion scale
. gen selfabort = VCF0806
{txt}(25,364 missing values generated)

{com}. replace selfabort = . if selfabort < 1
{txt}(4,718 real changes made, 4,718 to missing)

{com}. replace selfabort = . if selfabort > 4
{txt}(10,536 real changes made, 10,536 to missing)

{com}. label define abortlab 1 "Never be permitted" 4 "Always permitted"
{txt}
{com}. label values selfabort abortlab
{txt}
{com}. 
. 
. * Do whatever is necessary for equal opportunity
. * Note: This variable is reverse coded so that higher values indicate
. * more conservative attitudes
. gen equalopp = VCF9013 - 1
{txt}(29,972 missing values generated)

{com}. replace equalopp = . if equalopp > 4
{txt}(2,644 real changes made, 2,644 to missing)

{com}. label define equalopportunity 0 "0 Agree strongly" 1 "1 Agree somewhat" ///
>         2 "2 Neither agree nor disagree" 3 "3 Disagree somewhat" ///
>         4 "4 Disagree strongly"
{txt}
{com}. label values equalopp equalopportunity
{txt}
{com}. 
. 
. * Have gone too far pushing equal rights
. * Note: This variable is reverse coded so that higher values indicate
. * more conservative attitudes
. gen equalrights = VCF9014
{txt}(29,871 missing values generated)

{com}. replace equalrights = . if equalrights > 5
{txt}(2,614 real changes made, 2,614 to missing)

{com}. recode equalrights (5=0) (4=1) (3=2) (2=3) (1=4)
{txt}(equalrights: 20509 changes made)

{com}. label define equalrightspush 0 "0 Disagree strongly" 1 "1 Disagree somewhat" /// 
>         2 "2 Neither agree nor disagree" 3 "3 Agree somewhat" 4 "4 Agree strongly"
{txt}
{com}. label values equalrights equalrightspush
{txt}
{com}. 
. 
. * Big problem is not giving everyone an equal chance*
. gen equalchance = VCF9015 - 1
{txt}(31,152 missing values generated)

{com}. replace equalchance = . if equalchance > 4
{txt}(2,586 real changes made, 2,586 to missing)

{com}. label define equalchances 0 "0 Agree strongly" 1 "1 Agree somewhat" ///
>         2 "2 Neither agree nor disagree" 3 "3 Disagree somewhat" ///
>         4 "4 Disagree strongly"
{txt}
{com}. label values equalchance equalchances
{txt}
{com}. 
. 
. * Better off if we worried less about equality
. * Note: This variable is reverse coded so that higher values indicate
. * more conservative attitudes
. gen lessequal = VCF9017
{txt}(29,972 missing values generated)

{com}. replace lessequal = . if lessequal > 5
{txt}(2,770 real changes made, 2,770 to missing)

{com}. recode lessequal (5=0) (4=1) (3=2) (2=3) (1=4)
{txt}(lessequal: 20252 changes made)

{com}. label define lessequality 0 "0 Disagree strongly" 1 "1 Disagree somewhat" /// 
>         2 "2 Neither agree nor disagree" 3 "3 Agree somewhat" 4 "4 Agree strongly"
{txt}
{com}. label values lessequal lessequality
{txt}
{com}. 
. 
. * Not that big of a problem if people have more of a chance
. * Note: This variable is reverse coded so that higher values indicate
. * more conservative attitudes ???????
. gen unequal = VCF9016
{txt}(29,972 missing values generated)

{com}. replace unequal = . if unequal > 5
{txt}(2,813 real changes made, 2,813 to missing)

{com}. recode unequal (5=0) (4=1) (3=2) (2=3) (1=4)
{txt}(unequal: 20209 changes made)

{com}. label define unequalchance 0 "0 Disagree strongly" 1 "1 Disagree somewhat" ///
>         2 "2 Neither agree nor disagree" 3 "3 Agree somewhat" 4 "4 Agree strongly"
{txt}
{com}. label values unequal unequalchance
{txt}
{com}. 
. 
. * Many fewer problems if people were treated equally
. gen fewer = VCF9018 - 1
{txt}(28,691 missing values generated)

{com}. replace fewer = . if fewer > 4
{txt}(2,735 real changes made, 2,735 to missing)

{com}. label define fewerproblems 0 "0 Agree strongly" 1 "1 Agree somewhat" ///
>         2 "2 Neither agree nor disagree" 3 "3 Disagree somewhat" ///
>         4 "4 Disagree strongly"
{txt}
{com}. label values fewer fewerproblems
{txt}
{com}. 
. 
. * Adjusting views of moral behavior
. gen changing = VCF0852 - 1
{txt}(30,948 missing values generated)

{com}. replace changing = . if changing > 4
{txt}(2,718 real changes made, 2,718 to missing)

{com}. label define changingmorals 0 "Agree strongly" 1 "Agree somewhat" ///
>         2 "Neither agree nor disagree" 3 "Disagree somewhat" 4 "Disagree strongly"
{txt}
{com}. label values changing changingmorals
{txt}
{com}.  
.  
. * Newer lifestyles contributing to a breakdown in society
. * Note: This variable is reverse coded so that higher values indicate*
. * more conservative attitudes
. gen lifestyles = VCF0851
{txt}(30,948 missing values generated)

{com}. replace lifestyles = . if lifestyles > 5
{txt}(2,811 real changes made, 2,811 to missing)

{com}. recode lifestyles (5=0) (4=1) (3=2) (2=3) (1=4)
{txt}(lifestyles: 19235 changes made)

{com}. label define lifestylesnew 0 "0 Disagree strongly" 1 "1 Disagree somewhat" /// 
>         2 "2 Neither agree nor disagree"  3 "3 Agree somewhat" 4 "4 Agree strongly"
{txt}
{com}. label values lifestyles lifestylesnew
{txt}
{com}. 
. 
. * Tolerant of people who choose to live according to their own moral standards
. gen standards = VCF0854 - 1
{txt}(30,948 missing values generated)

{com}. replace standards = . if standards > 4
{txt}(2,756 real changes made, 2,756 to missing)

{com}. label define standardsown 0 "0 Agree strongly" 1 "1 Agree somewhat" ///
>         2 "2 Neither agree nor disagree" 3 "3 Disagree somewhat" ///
>         4 "4 Disagree strongly"
{txt}
{com}. label values standards standardsown
{txt}
{com}.  
.  
. * More emphasis on traditional family ties*
. * Note: This variable is reverse coded so that higher values indicate
. * more conservative attitudes
. gen family = VCF0853
{txt}(30,948 missing values generated)

{com}. replace family = . if family > 5
{txt}(2,720 real changes made, 2,720 to missing)

{com}. recode family (5=0) (4=1) (3=2) (2=3) (1=4)
{txt}(family: 19326 changes made)

{com}. label define familyties 0 "0 Disagree strongly" 1 "1 Disagree somewhat" /// 
>         2 "2 Neither agree nor disagree"  3 "3 Agree somewhat" 4 "4 Agree strongly"
{txt}
{com}. label values family familyties
{txt}
{com}. 
. 
. * Creating values scales
. alpha equalopp equalrights equalchance lessequal unequal fewer changing ///
>         lifestyles standards family, detail item generate(values) casewise

{txt}Test scale = mean(unstandardized items)

                                                            average
                             item-test     item-rest       interitem
Item         {c |}  Obs  Sign   correlation   correlation     covariance      alpha
{hline 13}{c +}{hline 65}
equalopp{col 14}{c |}{res}{col 16}16496{col 24}+{col 31} 0.4395{col 45} 0.3132{col 59} .3183787{col 73} 0.6866
{txt}equalrights{col 14}{c |}{res}{col 16}16496{col 24}+{col 31} 0.6142{col 45} 0.4527{col 59} .2680883{col 73} 0.6603
{txt}equalchance{col 14}{c |}{res}{col 16}16496{col 24}+{col 31} 0.5475{col 45} 0.3798{col 59} .2861794{col 73} 0.6747
{txt}lessequal{col 14}{c |}{res}{col 16}16496{col 24}+{col 31} 0.5862{col 45} 0.4192{col 59} .2753363{col 73} 0.6671
{txt}unequal{col 14}{c |}{res}{col 16}16496{col 24}+{col 31} 0.5098{col 45} 0.3432{col 59} .2962261{col 73} 0.6812
{txt}fewer{col 14}{c |}{res}{col 16}16496{col 24}+{col 31} 0.5290{col 45} 0.3746{col 59} .2934683{col 73} 0.6758
{txt}changing{col 14}{c |}{res}{col 16}16496{col 24}+{col 31} 0.4933{col 45} 0.2997{col 59}  .297759{col 73} 0.6910
{txt}lifestyles{col 14}{c |}{res}{col 16}16496{col 24}+{col 31} 0.4968{col 45} 0.3382{col 59} .3006025{col 73} 0.6820
{txt}standards{col 14}{c |}{res}{col 16}16496{col 24}+{col 31} 0.5219{col 45} 0.3635{col 59} .2944823{col 73} 0.6777
{txt}family{col 14}{c |}{res}{col 16}16496{col 24}+{col 31} 0.4580{col 45} 0.3190{col 59} .3124644{col 73} 0.6852
{txt}{hline 13}{c +}{hline 65}
Test scale{col 14}{c |}{res}{col 59} .2942985{col 73} 0.7010
{txt}{hline 13}{c BT}{hline 65}

Interitem covariances (obs=16496 in all pairs)

                equalopp  equalrights  equalchance    lessequal      unequal
   equalopp  {res}     0.8615
{txt}equalrights  {res}     0.2124       1.9148
{txt}equalchance  {res}     0.3822       0.3533       1.7454
{txt}  lessequal  {res}     0.2303       0.9296       0.3140       1.8892
{txt}    unequal  {res}     0.1987       0.6098       0.2838       0.7475       1.6039
{txt}      fewer  {res}     0.3765       0.3318       0.7742       0.2850       0.2776
{txt}   changing  {res}     0.1934       0.1666       0.3818       0.0711      -0.0056
{txt} lifestyles  {res}     0.0204       0.3983       0.0778       0.3175       0.2034
{txt}  standards  {res}     0.1693       0.2802       0.2748       0.1748       0.1043
{txt}     family  {res}    -0.0014       0.3103       0.0991       0.2615       0.1597

             {txt}      fewer     changing   lifestyles    standards       family
      fewer  {res}     1.4535
{txt}   changing  {res}     0.3213       2.0329
{txt} lifestyles  {res}     0.0450       0.3839       1.4362
{txt}  standards  {res}     0.2568       0.7045       0.4025       1.5011
{txt}     family  {res}     0.0104       0.3072       0.5730       0.2749       1.0584
{txt}
{com}. 
. alpha equalopp equalrights equalchance lessequal unequal fewer, ///
>         detail item generate(equality) casewise

{txt}Test scale = mean(unstandardized items)

                                                            average
                             item-test     item-rest       interitem
Item         {c |}  Obs  Sign   correlation   correlation     covariance      alpha
{hline 13}{c +}{hline 65}
equalopp{col 14}{c |}{res}{col 16}18820{col 24}+{col 31} 0.5081{col 45} 0.3392{col 59} .4808341{col 73} 0.6564
{txt}equalrights{col 14}{c |}{res}{col 16}18820{col 24}+{col 31} 0.6675{col 45} 0.4449{col 59} .3744032{col 73} 0.6198
{txt}equalchance{col 14}{c |}{res}{col 16}18820{col 24}+{col 31} 0.6156{col 45} 0.3861{col 59} .4089595{col 73} 0.6412
{txt}lessequal{col 14}{c |}{res}{col 16}18820{col 24}+{col 31} 0.6761{col 45} 0.4589{col 59} .3691694{col 73} 0.6143
{txt}unequal{col 14}{c |}{res}{col 16}18820{col 24}+{col 31} 0.6138{col 45} 0.3979{col 59} .4118326{col 73} 0.6365
{txt}fewer{col 14}{c |}{res}{col 16}18820{col 24}+{col 31} 0.6137{col 45} 0.4102{col 59} .4142091{col 73} 0.6325
{txt}{hline 13}{c +}{hline 65}
Test scale{col 14}{c |}{res}{col 59} .4099013{col 73} 0.6755
{txt}{hline 13}{c BT}{hline 65}

Interitem covariances (obs=18820 in all pairs)

                equalopp  equalrights  equalchance    lessequal      unequal
   equalopp  {res}     0.8524
{txt}equalrights  {res}     0.2089       1.9343
{txt}equalchance  {res}     0.3655       0.3542       1.7839
{txt}  lessequal  {res}     0.2198       0.9137       0.3059       1.9076
{txt}    unequal  {res}     0.1850       0.5854       0.2673       0.7363       1.6094
{txt}      fewer  {res}     0.3609       0.3422       0.7661       0.2811       0.2562

             {txt}      fewer
      fewer  {res}     1.4613
{txt}
{com}. 
. alpha changing lifestyles standards family, detail item ///
>         generate(morality) casewise

{txt}Test scale = mean(unstandardized items)

                                                            average
                             item-test     item-rest       interitem
Item         {c |}  Obs  Sign   correlation   correlation     covariance      alpha
{hline 13}{c +}{hline 65}
changing{col 14}{c |}{res}{col 16}19068{col 24}+{col 31} 0.7076{col 45} 0.3753{col 59} .4335072{col 73} 0.5849
{txt}lifestyles{col 14}{c |}{res}{col 16}19068{col 24}+{col 31} 0.6991{col 45} 0.4298{col 59} .4276876{col 73} 0.5348
{txt}standards{col 14}{c |}{res}{col 16}19068{col 24}+{col 31} 0.6961{col 45} 0.4224{col 59} .4321471{col 73} 0.5400
{txt}family{col 14}{c |}{res}{col 16}19068{col 24}+{col 31} 0.6460{col 45} 0.4044{col 59} .4965483{col 73} 0.5589
{txt}{hline 13}{c +}{hline 65}
Test scale{col 14}{c |}{res}{col 59} .4474725{col 73} 0.6237
{txt}{hline 13}{c BT}{hline 65}

Interitem covariances (obs=19068 in all pairs)

              changing  lifestyles   standards      family
  changing  {res}    2.0395
{txt}lifestyles  {res}    0.3835      1.4775
{txt} standards  {res}    0.6937      0.4124      1.5001
{txt}    family  {res}    0.3071      0.6058      0.2823      1.0922
{txt}
{com}.         
. gen valuediff = equality - morality     
{txt}(36,498 missing values generated)

{com}. gen absvaluediff = abs(valuediff)
{txt}(36,498 missing values generated)

{com}. 
. 
. * Value "polarization", or extremity
. gen valuepold = .
{txt}(52,994 missing values generated)

{com}. gen valuepolr = .       
{txt}(52,994 missing values generated)

{com}.         
. levelsof year, local(lev)       
{res}{txt}1948 1952 1954 1956 1958 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2008 2012 2016

{com}.         
. foreach i of local lev {c -(}
{txt}  2{com}. sum values if values != . & rep == 1 & year == `i', meanonly
{txt}  3{com}. replace valuepold = values - r(mean) if values != . & rep == 0 & year == `i'
{txt}  4{com}. sum values if values != . & rep == 0 & year == `i', meanonly
{txt}  5{com}. replace valuepolr = values - r(mean) if values != . & rep == 1 & year == `i'
{txt}  6{com}. {c )-}
{txt}(0 real changes made)
(0 real changes made)
(0 real changes made)
(0 real changes made)
(0 real changes made)
(0 real changes made)
(0 real changes made)
(0 real changes made)
(0 real changes made)
(0 real changes made)
(0 real changes made)
(0 real changes made)
(0 real changes made)
(0 real changes made)
(0 real changes made)
(0 real changes made)
(0 real changes made)
(0 real changes made)
(0 real changes made)
(0 real changes made)
(0 real changes made)
(0 real changes made)
(0 real changes made)
(0 real changes made)
(0 real changes made)
(0 real changes made)
(0 real changes made)
(0 real changes made)
(0 real changes made)
(0 real changes made)
(0 real changes made)
(0 real changes made)
(0 real changes made)
(0 real changes made)
(0 real changes made)
(0 real changes made)
(1,021 real changes made)
(734 real changes made)
(800 real changes made)
(690 real changes made)
(463 real changes made)
(359 real changes made)
(1,069 real changes made)
(825 real changes made)
(793 real changes made)
(729 real changes made)
(786 real changes made)
(585 real changes made)
(0 real changes made)
(0 real changes made)
(733 real changes made)
(590 real changes made)
(0 real changes made)
(0 real changes made)
(495 real changes made)
(440 real changes made)
(1,207 real changes made)
(593 real changes made)
(1,134 real changes made)
(520 real changes made)
(0 real changes made)
(0 real changes made)

{com}. 
. replace valuepold = abs(valuepold)
{txt}(7,086 real changes made)

{com}. replace valuepolr = abs(valuepolr)
{txt}(1,155 real changes made)

{com}. egen valuepol = rowmax(valuepold valuepolr)
{txt}(38428 missing values generated)

{com}. 
. 
. * Vote choice
. gen prezvote = VCF0704
{txt}(20,724 missing values generated)

{com}. replace prezvote = . if prezvote == 0
{txt}(11,579 real changes made, 11,579 to missing)

{com}. label define prezvotelab 1 "Democrat" 2 "Republican" 3 "Third party"
{txt}
{com}. label values prez prezvotelab
{txt}
{com}. 
. gen votedum = prezvote - 1
{txt}(32,303 missing values generated)

{com}. replace votedum = . if votedum == 2
{txt}(580 real changes made, 580 to missing)

{com}. 
. gen yesvote = VCF0702 - 1
{txt}(1,139 missing values generated)

{com}. replace yesvote = . if yesvote < 0 | yesvote > 1
{txt}(3,680 real changes made, 3,680 to missing)

{com}. 
. gen congvote = VCF0707
{txt}(1,801 missing values generated)

{com}. replace congvote = . if congvote == 0
{txt}(24,394 real changes made, 24,394 to missing)

{com}. label define votelab 1 "Democrat" 2 "Republican"
{txt}
{com}. label values congvote votelab
{txt}
{com}. 
. gen senvote = VCF0708
{txt}(3,098 missing values generated)

{com}. replace senvote = . if senvote == 0
{txt}(31,495 real changes made, 31,495 to missing)

{com}. label values senvote votelab
{txt}
{com}. 
. 
. * Level of information, as assessed by interviewer
. gen info = VCF0050a
{txt}(26,311 missing values generated)

{com}. replace info = . if info == 9
{txt}(290 real changes made, 290 to missing)

{com}. recode info (1=5) (2=4) (3=3) (4=2) (5=1)
{txt}(info: 17425 changes made)

{com}. label define infolab 1 "Very low" 2 "Fairly Low" 3 "Average" ///
>         4 "Fairly High" 5 "Very High"
{txt}
{com}. label values info infolab
{txt}
{com}. 
. 
. * Interest in campaigns (1 Hardly at all - 4 Most of the time)
. gen interest = VCF0310
{txt}(3,376 missing values generated)

{com}. replace interest = . if VCF0310 == 0
{txt}(1,464 real changes made, 1,464 to missing)

{com}. replace interest = . if VCF0310 == 9
{txt}(15 real changes made, 15 to missing)

{com}. label var interest "Interest in the the Campaigns"
{txt}
{com}. label define interestlab 1 "Not much interested" ///
>         2 "Somewhat interested" 3 "Very much interested"
{txt}
{com}. label values interest interestlab
{txt}
{com}. 
. 
. * External efficacy index (0 Least efficacious - 100 Most efficacious)
. gen efficacy = VCF0648
{txt}(5,554 missing values generated)

{com}. replace efficacy = . if efficacy == 999
{txt}(4,848 real changes made, 4,848 to missing)

{com}. 
. 
. * Trust in government index (0 Least trusting - 100 Most trusting)
. gen trust = VCF0656
{txt}(7,940 missing values generated)

{com}. replace trust = . if trust == 999
{txt}(3,996 real changes made, 3,996 to missing)

{com}. 
. 
. * Participation index (1 Lowest - 6 Highest)
. gen participate = VCF0723
{txt}(7,948 missing values generated)

{com}. replace participate = . if participate == 0
{txt}(3,531 real changes made, 3,531 to missing)

{com}. 
. 
. * Media exposure index (1 No media - 5 All four media)
. gen media = VCF0728
{txt}(25,492 missing values generated)

{com}. replace media = . if media == 0
{txt}(4,724 real changes made, 4,724 to missing)

{com}. 
. 
. * Sophistication scale
. factor info interest participate, factor(1) ipf
{txt}(obs=22,023)

Factor analysis/correlation{col 50}Number of obs    = {res}    22,023
{col 5}{txt}Method: iterated principal factors{col 50}Retained factors =   {res}       1
{col 5}{txt}Rotation: (unrotated){col 50}Number of params =   {res}       3

{txt}{col 5}{hline 13}{c TT}{hline 60}
{col 5}     Factor  {c |} {ralign 12:Eigenvalue}   Difference        Proportion   Cumulative
{col 5}{hline 13}{c +}{hline 60}
{col 5}{ralign 11:Factor1}  {c |}{res}      1.10092      1.10077            1.0000       1.0000
{txt}{col 5}{ralign 11:Factor2}  {c |}{res}      0.00015      0.00031            0.0001       1.0001
{txt}{col 5}{ralign 11:Factor3}  {c |}{res}     -0.00016            .           -0.0001       1.0000
{txt}{col 5}{hline 13}{c BT}{hline 60}
{col 5}LR test: independent vs. saturated:  chi2({res}3{txt})  ={res} 7916.02{txt} Prob>chi2 ={res} 0.0000

{txt}Factor loadings (pattern matrix) and unique variances

{space 4}{hline 13}{c  TT}{hline 10}{c  TT}{hline 14}
{space 4}{space 0}{ralign 12:Variable}{space 1}{c |}{space 1}{ralign 8:Factor1}{space 1}{c |}{space 1}{ralign 12:Uniqueness}{space 1}
{space 4}{hline 13}{c   +}{hline 10}{c   +}{hline 14}
{space 4}{space 0}{ralign 12:info}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.6227}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.6122}}}{space 1}
{space 4}{space 0}{ralign 12:interest}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.6891}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.5252}}}{space 1}
{space 4}{space 0}{ralign 12:participate}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.4881}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.7617}}}{space 1}
{space 4}{hline 13}{c  BT}{hline 10}{c  BT}{hline 14}

{com}. predict sophscale1
{txt}(regression scoring assumed)

{p 0 0 2}Scoring coefficients (method = regression){p_end}

{space 4}{hline 13}{c  TT}{hline 10}
{space 4}{space 0}{ralign 12:Variable}{space 1}{c |}{space 1}{ralign 8:Factor1}{space 1}
{space 4}{hline 13}{c   +}{hline 10}
{space 4}{space 0}{ralign 12:info}{space 1}{c |}{space 1}{ralign 8:{res:{sf: 0.35691}}}{space 1}
{space 4}{space 0}{ralign 12:interest}{space 1}{c |}{space 1}{ralign 8:{res:{sf: 0.46026}}}{space 1}
{space 4}{space 0}{ralign 12:participate}{space 1}{c |}{space 1}{ralign 8:{res:{sf: 0.22483}}}{space 1}
{space 4}{hline 13}{c  BT}{hline 10}


{com}. 
. factor interest participate if year == 1978, factor(1) ipf
{txt}(obs=2,288)

Factor analysis/correlation{col 50}Number of obs    = {res}     2,288
{col 5}{txt}Method: iterated principal factors{col 50}Retained factors =   {res}       1
{col 5}{txt}Rotation: (unrotated){col 50}Number of params =   {res}       1

{txt}{col 5}{hline 13}{c TT}{hline 60}
{col 5}     Factor  {c |} {ralign 12:Eigenvalue}   Difference        Proportion   Cumulative
{col 5}{hline 13}{c +}{hline 60}
{col 5}{ralign 11:Factor1}  {c |}{res}      0.72116      0.72128            1.0002       1.0002
{txt}{col 5}{ralign 11:Factor2}  {c |}{res}     -0.00011            .           -0.0002       1.0000
{txt}{col 5}{hline 13}{c BT}{hline 60}
{col 5}LR test: independent vs. saturated:  chi2({res}1{txt})  ={res}  318.58{txt} Prob>chi2 ={res} 0.0000

{txt}Factor loadings (pattern matrix) and unique variances

{space 4}{hline 13}{c  TT}{hline 10}{c  TT}{hline 14}
{space 4}{space 0}{ralign 12:Variable}{space 1}{c |}{space 1}{ralign 8:Factor1}{space 1}{c |}{space 1}{ralign 12:Uniqueness}{space 1}
{space 4}{hline 13}{c   +}{hline 10}{c   +}{hline 14}
{space 4}{space 0}{ralign 12:interest}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.6005}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.6394}}}{space 1}
{space 4}{space 0}{ralign 12:participate}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.6005}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.6394}}}{space 1}
{space 4}{hline 13}{c  BT}{hline 10}{c  BT}{hline 14}

{com}. predict sophscale2
{txt}(regression scoring assumed)

{p 0 0 2}Scoring coefficients (method = regression){p_end}

{space 4}{hline 13}{c  TT}{hline 10}
{space 4}{space 0}{ralign 12:Variable}{space 1}{c |}{space 1}{ralign 8:Factor1}{space 1}
{space 4}{hline 13}{c   +}{hline 10}
{space 4}{space 0}{ralign 12:interest}{space 1}{c |}{space 1}{ralign 8:{res:{sf: 0.44133}}}{space 1}
{space 4}{space 0}{ralign 12:participate}{space 1}{c |}{space 1}{ralign 8:{res:{sf: 0.44133}}}{space 1}
{space 4}{hline 13}{c  BT}{hline 10}


{com}. 
. factor interest participate if year == 1982, factor(1) ipf
{txt}(obs=1,405)

Factor analysis/correlation{col 50}Number of obs    = {res}     1,405
{col 5}{txt}Method: iterated principal factors{col 50}Retained factors =   {res}       1
{col 5}{txt}Rotation: (unrotated){col 50}Number of params =   {res}       1

{txt}{col 5}{hline 13}{c TT}{hline 60}
{col 5}     Factor  {c |} {ralign 12:Eigenvalue}   Difference        Proportion   Cumulative
{col 5}{hline 13}{c +}{hline 60}
{col 5}{ralign 11:Factor1}  {c |}{res}      0.72973      0.72984            1.0002       1.0002
{txt}{col 5}{ralign 11:Factor2}  {c |}{res}     -0.00011            .           -0.0002       1.0000
{txt}{col 5}{hline 13}{c BT}{hline 60}
{col 5}LR test: independent vs. saturated:  chi2({res}1{txt})  ={res}  200.57{txt} Prob>chi2 ={res} 0.0000

{txt}Factor loadings (pattern matrix) and unique variances

{space 4}{hline 13}{c  TT}{hline 10}{c  TT}{hline 14}
{space 4}{space 0}{ralign 12:Variable}{space 1}{c |}{space 1}{ralign 8:Factor1}{space 1}{c |}{space 1}{ralign 12:Uniqueness}{space 1}
{space 4}{hline 13}{c   +}{hline 10}{c   +}{hline 14}
{space 4}{space 0}{ralign 12:interest}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.6040}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.6351}}}{space 1}
{space 4}{space 0}{ralign 12:participate}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.6040}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.6351}}}{space 1}
{space 4}{hline 13}{c  BT}{hline 10}{c  BT}{hline 14}

{com}. predict sophscale3
{txt}(regression scoring assumed)

{p 0 0 2}Scoring coefficients (method = regression){p_end}

{space 4}{hline 13}{c  TT}{hline 10}
{space 4}{space 0}{ralign 12:Variable}{space 1}{c |}{space 1}{ralign 8:Factor1}{space 1}
{space 4}{hline 13}{c   +}{hline 10}
{space 4}{space 0}{ralign 12:interest}{space 1}{c |}{space 1}{ralign 8:{res:{sf: 0.44255}}}{space 1}
{space 4}{space 0}{ralign 12:participate}{space 1}{c |}{space 1}{ralign 8:{res:{sf: 0.44255}}}{space 1}
{space 4}{hline 13}{c  BT}{hline 10}


{com}. 
. factor interest participate if year == 1990, factor(1) ipf
{txt}(obs=1,975)

Factor analysis/correlation{col 50}Number of obs    = {res}     1,975
{col 5}{txt}Method: iterated principal factors{col 50}Retained factors =   {res}       1
{col 5}{txt}Rotation: (unrotated){col 50}Number of params =   {res}       1

{txt}{col 5}{hline 13}{c TT}{hline 60}
{col 5}     Factor  {c |} {ralign 12:Eigenvalue}   Difference        Proportion   Cumulative
{col 5}{hline 13}{c +}{hline 60}
{col 5}{ralign 11:Factor1}  {c |}{res}      0.67897      0.67908            1.0002       1.0002
{txt}{col 5}{ralign 11:Factor2}  {c |}{res}     -0.00011            .           -0.0002       1.0000
{txt}{col 5}{hline 13}{c BT}{hline 60}
{col 5}LR test: independent vs. saturated:  chi2({res}1{txt})  ={res}  241.74{txt} Prob>chi2 ={res} 0.0000

{txt}Factor loadings (pattern matrix) and unique variances

{space 4}{hline 13}{c  TT}{hline 10}{c  TT}{hline 14}
{space 4}{space 0}{ralign 12:Variable}{space 1}{c |}{space 1}{ralign 8:Factor1}{space 1}{c |}{space 1}{ralign 12:Uniqueness}{space 1}
{space 4}{hline 13}{c   +}{hline 10}{c   +}{hline 14}
{space 4}{space 0}{ralign 12:interest}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.5827}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.6605}}}{space 1}
{space 4}{space 0}{ralign 12:participate}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.5827}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.6605}}}{space 1}
{space 4}{hline 13}{c  BT}{hline 10}{c  BT}{hline 14}

{com}. predict sophscale4
{txt}(regression scoring assumed)

{p 0 0 2}Scoring coefficients (method = regression){p_end}

{space 4}{hline 13}{c  TT}{hline 10}
{space 4}{space 0}{ralign 12:Variable}{space 1}{c |}{space 1}{ralign 8:Factor1}{space 1}
{space 4}{hline 13}{c   +}{hline 10}
{space 4}{space 0}{ralign 12:interest}{space 1}{c |}{space 1}{ralign 8:{res:{sf: 0.43497}}}{space 1}
{space 4}{space 0}{ralign 12:participate}{space 1}{c |}{space 1}{ralign 8:{res:{sf: 0.43497}}}{space 1}
{space 4}{hline 13}{c  BT}{hline 10}


{com}. 
. factor interest participate if year == 1994, factor(1) ipf
{txt}(obs=1,768)

Factor analysis/correlation{col 50}Number of obs    = {res}     1,768
{col 5}{txt}Method: iterated principal factors{col 50}Retained factors =   {res}       1
{col 5}{txt}Rotation: (unrotated){col 50}Number of params =   {res}       1

{txt}{col 5}{hline 13}{c TT}{hline 60}
{col 5}     Factor  {c |} {ralign 12:Eigenvalue}   Difference        Proportion   Cumulative
{col 5}{hline 13}{c +}{hline 60}
{col 5}{ralign 11:Factor1}  {c |}{res}      0.64175      0.64186            1.0002       1.0002
{txt}{col 5}{ralign 11:Factor2}  {c |}{res}     -0.00011            .           -0.0002       1.0000
{txt}{col 5}{hline 13}{c BT}{hline 60}
{col 5}LR test: independent vs. saturated:  chi2({res}1{txt})  ={res}  192.01{txt} Prob>chi2 ={res} 0.0000

{txt}Factor loadings (pattern matrix) and unique variances

{space 4}{hline 13}{c  TT}{hline 10}{c  TT}{hline 14}
{space 4}{space 0}{ralign 12:Variable}{space 1}{c |}{space 1}{ralign 8:Factor1}{space 1}{c |}{space 1}{ralign 12:Uniqueness}{space 1}
{space 4}{hline 13}{c   +}{hline 10}{c   +}{hline 14}
{space 4}{space 0}{ralign 12:interest}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.5665}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.6791}}}{space 1}
{space 4}{space 0}{ralign 12:participate}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.5665}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.6791}}}{space 1}
{space 4}{hline 13}{c  BT}{hline 10}{c  BT}{hline 14}

{com}. predict sophscale5
{txt}(regression scoring assumed)

{p 0 0 2}Scoring coefficients (method = regression){p_end}

{space 4}{hline 13}{c  TT}{hline 10}
{space 4}{space 0}{ralign 12:Variable}{space 1}{c |}{space 1}{ralign 8:Factor1}{space 1}
{space 4}{hline 13}{c   +}{hline 10}
{space 4}{space 0}{ralign 12:interest}{space 1}{c |}{space 1}{ralign 8:{res:{sf: 0.42883}}}{space 1}
{space 4}{space 0}{ralign 12:participate}{space 1}{c |}{space 1}{ralign 8:{res:{sf: 0.42883}}}{space 1}
{space 4}{hline 13}{c  BT}{hline 10}


{com}. 
. egen sophistication = rowmax(sophscale*)
{txt}(14258 missing values generated)

{com}. 
. 
. * Elite polarization
. gen housepol = 0.492 if year == 1972
{txt}(50,289 missing values generated)

{com}. replace housepol = 0.499 if year == 1976
{txt}(2,248 real changes made)

{com}. replace housepol = 0.489 if year == 1978
{txt}(2,304 real changes made)

{com}. replace housepol = 0.514 if year == 1980
{txt}(1,614 real changes made)

{com}. replace housepol = 0.540 if year == 1982
{txt}(1,418 real changes made)

{com}. replace housepol = 0.573 if year == 1984
{txt}(2,257 real changes made)

{com}. replace housepol = 0.618 if year == 1988
{txt}(2,040 real changes made)

{com}. replace housepol = 0.634 if year == 1990
{txt}(1,980 real changes made)

{com}. replace housepol = 0.664 if year == 1992
{txt}(2,485 real changes made)

{com}. replace housepol = 0.727 if year == 1994
{txt}(1,795 real changes made)

{com}. replace housepol = 0.818 if year == 1996
{txt}(1,714 real changes made)

{com}. replace housepol = 0.877 if year == 2000
{txt}(1,807 real changes made)

{com}. replace housepol = 0.942 if year == 2004
{txt}(1,212 real changes made)

{com}. replace housepol = 1.091 if year == 2012
{txt}(2,054 real changes made)

{com}. 
. 
. keep caseid-housepol
{txt}
{com}. 
. 
. * Recode variables to range 0-1
. 
. levelsof year, local(lev)       
{res}{txt}1948 1952 1954 1956 1958 1960 1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2008 2012 2016

{com}.         
. foreach i of local lev {c -(}
{txt}  2{com}. foreach v of var ideostrength pidstrength demlike-repdislike ///
> ideothermdiff partydifftherm diffcandtherm valuepol perceivepol ///
> edu age sophistication income housepol pid ideo sorting ///
> trust efficacy participate interest affectpol issextreme{c -(} 
{txt}  3{com}.         su `v', meanonly 
{txt}  4{com}.         gen `v'2 = (`v' - r(min))/(r(max) - r(min)) 
{txt}  5{com}. {c )-}
{txt}  6{com}. {c )-}
{txt}(27,815 missing values generated)
(7,621 missing values generated)
(20,238 missing values generated)
(20,238 missing values generated)
(20,238 missing values generated)
(20,238 missing values generated)
(18,698 missing values generated)
(24,821 missing values generated)
(28,868 missing values generated)
(38,428 missing values generated)
(20,283 missing values generated)
(1,164 missing values generated)
(2,243 missing values generated)
(14,258 missing values generated)
(5,260 missing values generated)
(25,361 missing values generated)
(1,665 missing values generated)
(26,937 missing values generated)
(31,099 missing values generated)
(11,936 missing values generated)
(10,402 missing values generated)
(11,479 missing values generated)
(4,855 missing values generated)
(11,152 missing values generated)
(17,788 missing values generated)
{err}variable {bf}ideostrength2{sf} already defined
{txt}{search r(110), local:r(110);}

end of do-file

{search r(110), local:r(110);}

{com}. do "/var/folders/xb/ddtsf7g93xd57f7hhtnm9lyc0000gp/T//SD59652.000000"
{txt}
{com}. 
. ********************************************************************************
. 
. *** Supplemental Appendix Analyses ***
. 
. ****
. ** Show individual indicators over time
. ****
. 
. * Perceived
. bysort year: sum pdiffinsure pdiffdefense pdiffservice pdiffaid ///
>         pdiffjobs partyideodiff

{txt}{hline}
-> year = 1948

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}pdiffinsure {c |}{res}          0
{txt}pdiffdefense {c |}{res}          0
{txt}pdiffservice {c |}{res}          0
{txt}{space 4}pdiffaid {c |}{res}          0
{txt}{space 3}pdiffjobs {c |}{res}          0
{txt}{hline 13}{c +}{hline 57}
partyideod~f {c |}{res}          0

{txt}{hline}
-> year = 1952

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}pdiffinsure {c |}{res}          0
{txt}pdiffdefense {c |}{res}          0
{txt}pdiffservice {c |}{res}          0
{txt}{space 4}pdiffaid {c |}{res}          0
{txt}{space 3}pdiffjobs {c |}{res}          0
{txt}{hline 13}{c +}{hline 57}
partyideod~f {c |}{res}          0

{txt}{hline}
-> year = 1954

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}pdiffinsure {c |}{res}          0
{txt}pdiffdefense {c |}{res}          0
{txt}pdiffservice {c |}{res}          0
{txt}{space 4}pdiffaid {c |}{res}          0
{txt}{space 3}pdiffjobs {c |}{res}          0
{txt}{hline 13}{c +}{hline 57}
partyideod~f {c |}{res}          0

{txt}{hline}
-> year = 1956

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}pdiffinsure {c |}{res}          0
{txt}pdiffdefense {c |}{res}          0
{txt}pdiffservice {c |}{res}          0
{txt}{space 4}pdiffaid {c |}{res}          0
{txt}{space 3}pdiffjobs {c |}{res}          0
{txt}{hline 13}{c +}{hline 57}
partyideod~f {c |}{res}          0

{txt}{hline}
-> year = 1958

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}pdiffinsure {c |}{res}          0
{txt}pdiffdefense {c |}{res}          0
{txt}pdiffservice {c |}{res}          0
{txt}{space 4}pdiffaid {c |}{res}          0
{txt}{space 3}pdiffjobs {c |}{res}          0
{txt}{hline 13}{c +}{hline 57}
partyideod~f {c |}{res}          0

{txt}{hline}
-> year = 1960

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}pdiffinsure {c |}{res}          0
{txt}pdiffdefense {c |}{res}          0
{txt}pdiffservice {c |}{res}          0
{txt}{space 4}pdiffaid {c |}{res}          0
{txt}{space 3}pdiffjobs {c |}{res}          0
{txt}{hline 13}{c +}{hline 57}
partyideod~f {c |}{res}          0

{txt}{hline}
-> year = 1962

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}pdiffinsure {c |}{res}          0
{txt}pdiffdefense {c |}{res}          0
{txt}pdiffservice {c |}{res}          0
{txt}{space 4}pdiffaid {c |}{res}          0
{txt}{space 3}pdiffjobs {c |}{res}          0
{txt}{hline 13}{c +}{hline 57}
partyideod~f {c |}{res}          0

{txt}{hline}
-> year = 1964

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}pdiffinsure {c |}{res}          0
{txt}pdiffdefense {c |}{res}          0
{txt}pdiffservice {c |}{res}          0
{txt}{space 4}pdiffaid {c |}{res}          0
{txt}{space 3}pdiffjobs {c |}{res}          0
{txt}{hline 13}{c +}{hline 57}
partyideod~f {c |}{res}          0

{txt}{hline}
-> year = 1966

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}pdiffinsure {c |}{res}          0
{txt}pdiffdefense {c |}{res}          0
{txt}pdiffservice {c |}{res}          0
{txt}{space 4}pdiffaid {c |}{res}          0
{txt}{space 3}pdiffjobs {c |}{res}          0
{txt}{hline 13}{c +}{hline 57}
partyideod~f {c |}{res}          0

{txt}{hline}
-> year = 1968

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}pdiffinsure {c |}{res}          0
{txt}pdiffdefense {c |}{res}          0
{txt}pdiffservice {c |}{res}          0
{txt}{space 4}pdiffaid {c |}{res}          0
{txt}{space 3}pdiffjobs {c |}{res}          0
{txt}{hline 13}{c +}{hline 57}
partyideod~f {c |}{res}          0

{txt}{hline}
-> year = 1970

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}pdiffinsure {c |}{res}      1,012    1.561265    1.666924          0          6
{txt}pdiffdefense {c |}{res}          0
{txt}pdiffservice {c |}{res}          0
{txt}{space 4}pdiffaid {c |}{res}      1,176    1.646259    1.623981          0          6
{txt}{space 3}pdiffjobs {c |}{res}          0
{txt}{hline 13}{c +}{hline 57}
partyideod~f {c |}{res}          0

{txt}{hline}
-> year = 1972

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}pdiffinsure {c |}{res}        659    1.933232    1.833106          0          6
{txt}pdiffdefense {c |}{res}          0
{txt}pdiffservice {c |}{res}          0
{txt}{space 4}pdiffaid {c |}{res}      1,483     1.44909    1.499191          0          6
{txt}{space 3}pdiffjobs {c |}{res}      1,642    2.052375    1.716589          0          6
{txt}{hline 13}{c +}{hline 57}
partyideod~f {c |}{res}      1,383    2.167751    1.420616          0          6

{txt}{hline}
-> year = 1974

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}pdiffinsure {c |}{res}          0
{txt}pdiffdefense {c |}{res}          0
{txt}pdiffservice {c |}{res}          0
{txt}{space 4}pdiffaid {c |}{res}        914    1.496718    1.571407          0          6
{txt}{space 3}pdiffjobs {c |}{res}        981    1.982671    1.725767          0          6
{txt}{hline 13}{c +}{hline 57}
partyideod~f {c |}{res}        928    2.037716    1.461361          0          6

{txt}{hline}
-> year = 1976

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}pdiffinsure {c |}{res}      1,213    2.207749    1.831978          0          6
{txt}pdiffdefense {c |}{res}          0
{txt}pdiffservice {c |}{res}          0
{txt}{space 4}pdiffaid {c |}{res}      1,445    1.714879     1.65068          0          6
{txt}{space 3}pdiffjobs {c |}{res}      1,507    2.149967    1.777853          0          6
{txt}{hline 13}{c +}{hline 57}
partyideod~f {c |}{res}      1,334    2.512744    1.457907          0          6

{txt}{hline}
-> year = 1978

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}pdiffinsure {c |}{res}      1,255    1.886853    1.762613          0          6
{txt}pdiffdefense {c |}{res}          0
{txt}pdiffservice {c |}{res}          0
{txt}{space 4}pdiffaid {c |}{res}      1,533    1.460535    1.579252          0          6
{txt}{space 3}pdiffjobs {c |}{res}      1,445      1.7391    1.628741          0          6
{txt}{hline 13}{c +}{hline 57}
partyideod~f {c |}{res}      1,404    2.108262    1.450427          0          6

{txt}{hline}
-> year = 1980

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}pdiffinsure {c |}{res}          0
{txt}pdiffdefense {c |}{res}      1,065    1.974648    1.441306          0          6
{txt}pdiffservice {c |}{res}          0
{txt}{space 4}pdiffaid {c |}{res}        974      2.2423    1.498481          0          6
{txt}{space 3}pdiffjobs {c |}{res}        915    2.133333    1.582776          0          6
{txt}{hline 13}{c +}{hline 57}
partyideod~f {c |}{res}        896    2.569196     1.43683          0          6

{txt}{hline}
-> year = 1982

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}pdiffinsure {c |}{res}          0
{txt}pdiffdefense {c |}{res}        957    2.126437    1.417059          0          6
{txt}pdiffservice {c |}{res}        963    2.395639    1.605688          0          6
{txt}{space 4}pdiffaid {c |}{res}        981    2.146789     1.57948          0          6
{txt}{space 3}pdiffjobs {c |}{res}      1,022    2.276908    1.585511          0          6
{txt}{hline 13}{c +}{hline 57}
partyideod~f {c |}{res}        824    2.777913    1.414367          0          6

{txt}{hline}
-> year = 1984

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}pdiffinsure {c |}{res}          0
{txt}pdiffdefense {c |}{res}      1,672    2.325359     1.54583          0          6
{txt}pdiffservice {c |}{res}      1,674    2.544803    1.614552          0          6
{txt}{space 4}pdiffaid {c |}{res}      1,687     2.12211    1.613784          0          6
{txt}{space 3}pdiffjobs {c |}{res}      1,648    1.913835    1.600274          0          6
{txt}{hline 13}{c +}{hline 57}
partyideod~f {c |}{res}      1,776    2.600788    1.558974          0          6

{txt}{hline}
-> year = 1986

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}pdiffinsure {c |}{res}          0
{txt}pdiffdefense {c |}{res}      1,728    2.269097    1.490341          0          6
{txt}pdiffservice {c |}{res}      1,695    2.251327    1.636893          0          6
{txt}{space 4}pdiffaid {c |}{res}          0
{txt}{space 3}pdiffjobs {c |}{res}          0
{txt}{hline 13}{c +}{hline 57}
partyideod~f {c |}{res}      1,716    2.391608    1.483208          0          6

{txt}{hline}
-> year = 1988

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}pdiffinsure {c |}{res}      1,225    2.360816    1.704598          0          6
{txt}pdiffdefense {c |}{res}      1,557    2.024406    1.492714          0          6
{txt}pdiffservice {c |}{res}      1,557    1.971098    1.509971          0          6
{txt}{space 4}pdiffaid {c |}{res}      1,474    1.720488    1.576052          0          6
{txt}{space 3}pdiffjobs {c |}{res}      1,331    1.972201    1.617566          0          6
{txt}{hline 13}{c +}{hline 57}
partyideod~f {c |}{res}      1,501    2.693538    1.516361          0          6

{txt}{hline}
-> year = 1990

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}pdiffinsure {c |}{res}          0
{txt}pdiffdefense {c |}{res}      1,361    2.018369     1.53406          0          6
{txt}pdiffservice {c |}{res}      1,325    1.893585     1.61142          0          6
{txt}{space 4}pdiffaid {c |}{res}      1,378    1.800435    1.605211          0          6
{txt}{space 3}pdiffjobs {c |}{res}          0
{txt}{hline 13}{c +}{hline 57}
partyideod~f {c |}{res}      1,519    2.347597    1.525037          0          6

{txt}{hline}
-> year = 1992

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}pdiffinsure {c |}{res}          0
{txt}pdiffdefense {c |}{res}      1,904    1.920693    1.476213          0          6
{txt}pdiffservice {c |}{res}      1,924    2.264033    1.635518          0          6
{txt}{space 4}pdiffaid {c |}{res}          0
{txt}{space 3}pdiffjobs {c |}{res}      1,703    2.204932    1.690417          0          6
{txt}{hline 13}{c +}{hline 57}
partyideod~f {c |}{res}      1,999    2.729865     1.60332          0          6

{txt}{hline}
-> year = 1994

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}pdiffinsure {c |}{res}      1,453    2.705437    1.847477          0          6
{txt}pdiffdefense {c |}{res}          0
{txt}pdiffservice {c |}{res}      1,407    2.158493    1.731159          0          6
{txt}{space 4}pdiffaid {c |}{res}      1,440    1.863889    1.665436          0          6
{txt}{space 3}pdiffjobs {c |}{res}      1,465    2.284642    1.750157          0          6
{txt}{hline 13}{c +}{hline 57}
partyideod~f {c |}{res}      1,522    2.579501    1.533514          0          6

{txt}{hline}
-> year = 1996

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}pdiffinsure {c |}{res}          0
{txt}pdiffdefense {c |}{res}      1,360    1.902206    1.402718          0          6
{txt}pdiffservice {c |}{res}      1,400        2.52    1.574329          0          6
{txt}{space 4}pdiffaid {c |}{res}          0
{txt}{space 3}pdiffjobs {c |}{res}          0
{txt}{hline 13}{c +}{hline 57}
partyideod~f {c |}{res}      1,551    2.703417    1.483582          0          6

{txt}{hline}
-> year = 1998

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}pdiffinsure {c |}{res}          0
{txt}pdiffdefense {c |}{res}          0
{txt}pdiffservice {c |}{res}      1,096    2.310219    1.707498          0          6
{txt}{space 4}pdiffaid {c |}{res}          0
{txt}{space 3}pdiffjobs {c |}{res}          0
{txt}{hline 13}{c +}{hline 57}
partyideod~f {c |}{res}      1,108    2.543321    1.457287          0          6

{txt}{hline}
-> year = 2000

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}pdiffinsure {c |}{res}          0
{txt}pdiffdefense {c |}{res}        832    1.861779    1.493308          0          6
{txt}pdiffservice {c |}{res}        882    2.354875    1.586666          0          6
{txt}{space 4}pdiffaid {c |}{res}        810    2.134568    1.727525          0          6
{txt}{space 3}pdiffjobs {c |}{res}        829    2.235223    1.668525          0          6
{txt}{hline 13}{c +}{hline 57}
partyideod~f {c |}{res}      1,343    2.932241     1.44415          0          6

{txt}{hline}
-> year = 2002

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}pdiffinsure {c |}{res}          0
{txt}pdiffdefense {c |}{res}          0
{txt}pdiffservice {c |}{res}          0
{txt}{space 4}pdiffaid {c |}{res}          0
{txt}{space 3}pdiffjobs {c |}{res}          0
{txt}{hline 13}{c +}{hline 57}
partyideod~f {c |}{res}          0

{txt}{hline}
-> year = 2004

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}pdiffinsure {c |}{res}          0
{txt}pdiffdefense {c |}{res}      1,108    2.270758    1.557327          0          6
{txt}pdiffservice {c |}{res}      1,096    2.465328    1.667493          0          6
{txt}{space 4}pdiffaid {c |}{res}      1,008     2.22123    1.770234          0          6
{txt}{space 3}pdiffjobs {c |}{res}      1,073    2.442684     1.77533          0          6
{txt}{hline 13}{c +}{hline 57}
partyideod~f {c |}{res}      1,083     2.99169    1.566435          0          6

{txt}{hline}
-> year = 2008

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}pdiffinsure {c |}{res}          0
{txt}pdiffdefense {c |}{res}          0
{txt}pdiffservice {c |}{res}          0
{txt}{space 4}pdiffaid {c |}{res}          0
{txt}{space 3}pdiffjobs {c |}{res}          0
{txt}{hline 13}{c +}{hline 57}
partyideod~f {c |}{res}      2,100    2.889048    1.754752          0          6

{txt}{hline}
-> year = 2012

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}pdiffinsure {c |}{res}      1,830    3.197814    1.884353          0          6
{txt}pdiffdefense {c |}{res}          0
{txt}pdiffservice {c |}{res}      1,882    2.881509    1.842925          0          6
{txt}{space 4}pdiffaid {c |}{res}          0
{txt}{space 3}pdiffjobs {c |}{res}      1,839    2.957586    1.919871          0          6
{txt}{hline 13}{c +}{hline 57}
partyideod~f {c |}{res}      1,827    3.279693    1.729215          0          6

{txt}{hline}
-> year = 2016

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}pdiffinsure {c |}{res}          0
{txt}pdiffdefense {c |}{res}          0
{txt}pdiffservice {c |}{res}          0
{txt}{space 4}pdiffaid {c |}{res}          0
{txt}{space 3}pdiffjobs {c |}{res}          0
{txt}{hline 13}{c +}{hline 57}
partyideod~f {c |}{res}      1,102    3.166969    1.666379          0          6

{txt}
{com}.         
. alpha pdiffinsure pdiffdefense pdiffservice pdiffaid ///
>         pdiffjobs partyideodiff

{txt}Test scale = mean(unstandardized items)

Average interitem covariance:{col 34}{res} 1.368159
{txt}Number of items in the scale:{col 34}{res}        6
{txt}Scale reliability coefficient:{col 34}{res}   0.8589
{txt}
{com}.         
. factor pdiffinsure pdiffdefense pdiffservice pdiffaid ///
>         pdiffjobs partyideodiff, ipf
{txt}(obs=892)

Factor analysis/correlation{col 50}Number of obs    = {res}       892
{col 5}{txt}Method: iterated principal factors{col 50}Retained factors =   {res}       5
{col 5}{txt}Rotation: (unrotated){col 50}Number of params =   {res}      15

{txt}{col 5}{hline 13}{c TT}{hline 60}
{col 5}     Factor  {c |} {ralign 12:Eigenvalue}   Difference        Proportion   Cumulative
{col 5}{hline 13}{c +}{hline 60}
{col 5}{ralign 11:Factor1}  {c |}{res}      3.01265      2.71348            0.8561       0.8561
{txt}{col 5}{ralign 11:Factor2}  {c |}{res}      0.29916      0.19434            0.0850       0.9411
{txt}{col 5}{ralign 11:Factor3}  {c |}{res}      0.10483      0.02359            0.0298       0.9709
{txt}{col 5}{ralign 11:Factor4}  {c |}{res}      0.08123      0.05969            0.0231       0.9939
{txt}{col 5}{ralign 11:Factor5}  {c |}{res}      0.02154      0.02177            0.0061       1.0001
{txt}{col 5}{ralign 11:Factor6}  {c |}{res}     -0.00023            .           -0.0001       1.0000
{txt}{col 5}{hline 13}{c BT}{hline 60}
{col 5}LR test: independent vs. saturated:  chi2({res}15{txt}) ={res} 1984.80{txt} Prob>chi2 ={res} 0.0000

{txt}Factor loadings (pattern matrix) and unique variances

{space 4}{hline 13}{c  TT}{hline 10}{hline 10}{hline 10}{hline 10}{hline 10}
{space 4}{space 0}{ralign 12:Variable}{space 1}{c |}{space 1}{ralign 8:Factor1}{space 1}{space 1}{ralign 8:Factor2}{space 1}{space 1}{ralign 8:Factor3}{space 1}{space 1}{ralign 8:Factor4}{space 1}{space 1}{ralign 8:Factor5}{space 1}
{space 4}{hline 13}{c   +}{hline 10}{hline 10}{hline 10}{hline 10}{hline 10}
{space 4}{space 0}{ralign 12:pdiffinsure}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.7319}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.1038}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0685}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.2157}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0003}}}{space 1}
{space 4}{space 0}{ralign 12:pdiffdefense}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.6978}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.2701}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.1335}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0654}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0606}}}{space 1}
{space 4}{space 0}{ralign 12:pdiffservice}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.7383}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.2332}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.2006}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0141}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0260}}}{space 1}
{space 4}{space 0}{ralign 12:pdiffaid}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.7446}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.1877}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0869}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.1652}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0622}}}{space 1}
{space 4}{space 0}{ralign 12:pdiffjobs}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.7857}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.3049}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.1240}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0087}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0498}}}{space 1}
{space 4}{space 0}{ralign 12:partyideod~f}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.5227}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.1812}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.1385}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0535}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.1042}}}{space 1}
{space 4}{hline 13}{c  BT}{hline 10}{hline 10}{hline 10}{hline 10}{hline 10}

{space 4}{hline 13}{c  TT}{hline 14}
{space 4}{space 0}{ralign 12:Variable}{space 1}{c |}{space 1}{ralign 12:Uniqueness}{space 1}
{space 4}{hline 13}{c   +}{hline 14}
{space 4}{space 0}{ralign 12:pdiffinsure}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.4023}}}{space 1}
{space 4}{space 0}{ralign 12:pdiffdefense}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.4144}}}{space 1}
{space 4}{space 0}{ralign 12:pdiffservice}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.3595}}}{space 1}
{space 4}{space 0}{ralign 12:pdiffaid}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.3717}}}{space 1}
{space 4}{space 0}{ralign 12:pdiffjobs}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.2717}}}{space 1}
{space 4}{space 0}{ralign 12:partyideod~f}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.6610}}}{space 1}
{space 4}{hline 13}{c  BT}{hline 14}

{com}.         
. pwcorr pdiffinsure pdiffdefense pdiffservice pdiffaid ///
>         pdiffjobs partyideodiff if rep != .

             {txt}{c |} pdiffi~e pdiffd~e pdiffs~e pdiffaid pdiffj~s partyi~f
{hline 13}{c +}{hline 54}
 pdiffinsure {c |} {res}  1.0000 
{txt}pdiffdefense {c |} {res}  0.4691   1.0000 
{txt}pdiffservice {c |} {res}  0.5816   0.5051   1.0000 
    {txt}pdiffaid {c |} {res}  0.5475   0.4601   0.6099   1.0000 
   {txt}pdiffjobs {c |} {res}  0.5883   0.4617   0.5881   0.5876   1.0000 
{txt}partyideod~f {c |} {res}  0.4894   0.3900   0.4543   0.4327   0.4278   1.0000 
{txt}
{com}. di (0.4691 + 0.5816 + 0.5475 + 0.5883 + 0.4894 + 0.5051 ///
>         + 0.4601 + 0.4617 + 0.39 + 0.6099 + 0.5881 + 0.4543 ///
>         + 0.5876 + 0.4327 + 0.4278)/15
{res}.50621333
{txt}
{com}.         
. * Affective
. bysort year: sum ideothermdiff partydifftherm diffcandtherm if rep != .

{txt}{hline}
-> year = 1948

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
ideothermd~f {c |}{res}          0
{txt}partydifft~m {c |}{res}          0
{txt}diffcandth~m {c |}{res}          0

{txt}{hline}
-> year = 1952

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
ideothermd~f {c |}{res}          0
{txt}partydifft~m {c |}{res}          0
{txt}diffcandth~m {c |}{res}          0

{txt}{hline}
-> year = 1954

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
ideothermd~f {c |}{res}          0
{txt}partydifft~m {c |}{res}          0
{txt}diffcandth~m {c |}{res}          0

{txt}{hline}
-> year = 1956

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
ideothermd~f {c |}{res}          0
{txt}partydifft~m {c |}{res}          0
{txt}diffcandth~m {c |}{res}          0

{txt}{hline}
-> year = 1958

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
ideothermd~f {c |}{res}          0
{txt}partydifft~m {c |}{res}          0
{txt}diffcandth~m {c |}{res}          0

{txt}{hline}
-> year = 1960

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
ideothermd~f {c |}{res}          0
{txt}partydifft~m {c |}{res}          0
{txt}diffcandth~m {c |}{res}          0

{txt}{hline}
-> year = 1962

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
ideothermd~f {c |}{res}          0
{txt}partydifft~m {c |}{res}          0
{txt}diffcandth~m {c |}{res}          0

{txt}{hline}
-> year = 1964

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
ideothermd~f {c |}{res}      1,381    19.61188    23.81815          0         97
{txt}partydifft~m {c |}{res}          0
{txt}diffcandth~m {c |}{res}          0

{txt}{hline}
-> year = 1966

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
ideothermd~f {c |}{res}      1,082    18.22274     22.7607          0         97
{txt}partydifft~m {c |}{res}          0
{txt}diffcandth~m {c |}{res}          0

{txt}{hline}
-> year = 1968

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
ideothermd~f {c |}{res}      1,317    19.19438    22.00228          0         97
{txt}partydifft~m {c |}{res}          0
{txt}diffcandth~m {c |}{res}      1,157     31.1236    22.59772          0         97

{txt}{hline}
-> year = 1970

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
ideothermd~f {c |}{res}      1,127    25.33629    25.05361          0         97
{txt}partydifft~m {c |}{res}          0
{txt}diffcandth~m {c |}{res}          0

{txt}{hline}
-> year = 1972

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
ideothermd~f {c |}{res}      1,565     22.9016    22.73199          0         97
{txt}partydifft~m {c |}{res}          0
{txt}diffcandth~m {c |}{res}      2,203    41.88652    29.16259          0         97

{txt}{hline}
-> year = 1974

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
ideothermd~f {c |}{res}      1,106    22.91863    23.24165          0         97
{txt}partydifft~m {c |}{res}          0
{txt}diffcandth~m {c |}{res}          0

{txt}{hline}
-> year = 1976

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
ideothermd~f {c |}{res}      1,323    20.18216    21.87188          0         97
{txt}partydifft~m {c |}{res}          0
{txt}diffcandth~m {c |}{res}      1,811    32.74379    25.18121          0         97

{txt}{hline}
-> year = 1978

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
ideothermd~f {c |}{res}          0
{txt}partydifft~m {c |}{res}      1,723    23.71967    23.69686          0         97
{txt}diffcandth~m {c |}{res}          0

{txt}{hline}
-> year = 1980

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
ideothermd~f {c |}{res}      1,033    24.21007    23.90913          0         97
{txt}partydifft~m {c |}{res}      1,310    27.44351    25.39634          0         97
{txt}diffcandth~m {c |}{res}      1,301    34.64335    25.39919          0         97

{txt}{hline}
-> year = 1982

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
ideothermd~f {c |}{res}      1,045    20.78852    24.87652          0         97
{txt}partydifft~m {c |}{res}      1,181    30.77477    25.25672          0         97
{txt}diffcandth~m {c |}{res}          0

{txt}{hline}
-> year = 1984

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
ideothermd~f {c |}{res}      1,531    20.13063    21.57461          0         97
{txt}partydifft~m {c |}{res}      1,881    31.07656    26.64322          0         97
{txt}diffcandth~m {c |}{res}      1,903    40.13242    27.98201          0         97

{txt}{hline}
-> year = 1986

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
ideothermd~f {c |}{res}      1,641    23.45399    23.20151          0         97
{txt}partydifft~m {c |}{res}      1,796     29.9961    25.98331          0         97
{txt}diffcandth~m {c |}{res}          0

{txt}{hline}
-> year = 1988

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
ideothermd~f {c |}{res}      1,407    22.92466    22.67489          0         97
{txt}partydifft~m {c |}{res}      1,717     32.7053    26.81345          0         97
{txt}diffcandth~m {c |}{res}      1,721    36.58803    27.31803          0         97

{txt}{hline}
-> year = 1990

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
ideothermd~f {c |}{res}      1,524    21.51969    23.16781          0         97
{txt}partydifft~m {c |}{res}      1,656    25.95773    24.95682          0         97
{txt}diffcandth~m {c |}{res}          0

{txt}{hline}
-> year = 1992

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
ideothermd~f {c |}{res}      1,825    21.87616    22.65267          0         97
{txt}partydifft~m {c |}{res}      2,098    30.17302    24.74311          0         97
{txt}diffcandth~m {c |}{res}      2,110    35.49668    25.58091          0         97

{txt}{hline}
-> year = 1994

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
ideothermd~f {c |}{res}      1,471    26.19986    25.90668          0         97
{txt}partydifft~m {c |}{res}      1,567    30.24633    24.53461          0         97
{txt}diffcandth~m {c |}{res}          0

{txt}{hline}
-> year = 1996

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
ideothermd~f {c |}{res}      1,317    23.27866    22.96361          0         97
{txt}partydifft~m {c |}{res}      1,528    33.03599    26.06675          0         97
{txt}diffcandth~m {c |}{res}      1,524    39.04593    25.53358          0         97

{txt}{hline}
-> year = 1998

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
ideothermd~f {c |}{res}      1,041    23.72142    23.88492          0         97
{txt}partydifft~m {c |}{res}      1,104    32.59058    25.67481          0         97
{txt}diffcandth~m {c |}{res}          0

{txt}{hline}
-> year = 2000

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
ideothermd~f {c |}{res}      1,242      22.719    23.37559          0         97
{txt}partydifft~m {c |}{res}      1,525    33.18033    25.64434          0         97
{txt}diffcandth~m {c |}{res}      1,527    35.18664    25.60016          0         97

{txt}{hline}
-> year = 2002

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
ideothermd~f {c |}{res}      1,181    21.09483    23.17021          0         97
{txt}partydifft~m {c |}{res}          0
{txt}diffcandth~m {c |}{res}          0

{txt}{hline}
-> year = 2004

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
ideothermd~f {c |}{res}        898    23.57461    23.63319          0         97
{txt}partydifft~m {c |}{res}      1,055    35.72322    27.60248          0         97
{txt}diffcandth~m {c |}{res}      1,063    46.76388    28.24926          0         97

{txt}{hline}
-> year = 2008

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
ideothermd~f {c |}{res}      1,696    21.37087    22.41901          0         97
{txt}partydifft~m {c |}{res}      1,979    39.30571    29.20712          0         97
{txt}diffcandth~m {c |}{res}      1,990    41.01407    27.91139          0         97

{txt}{hline}
-> year = 2012

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
ideothermd~f {c |}{res}      1,621    23.95682    24.76825          0         97
{txt}partydifft~m {c |}{res}      1,798     42.1079    30.33564          0         97
{txt}diffcandth~m {c |}{res}      1,795      52.239    29.28968          0         97

{txt}{hline}
-> year = 2016

    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
ideothermd~f {c |}{res}        918    29.39869    26.93095          0         97
{txt}partydifft~m {c |}{res}      1,029    36.48008    27.69172          0         97
{txt}diffcandth~m {c |}{res}      1,043    53.44966    29.09337          0         97

{txt}
{com}. 
. alpha ideothermdiff partydifftherm diffcandtherm if year > 1970

{txt}Test scale = mean(unstandardized items)

Average interitem covariance:{col 34}{res} 284.7578
{txt}Number of items in the scale:{col 34}{res}        3
{txt}Scale reliability coefficient:{col 34}{res}   0.6876
{txt}
{com}. 
. factor ideothermdiff partydifftherm diffcandtherm, ipf
{txt}(obs=14,668)

Factor analysis/correlation{col 50}Number of obs    = {res}    14,668
{col 5}{txt}Method: iterated principal factors{col 50}Retained factors =   {res}       2
{col 5}{txt}Rotation: (unrotated){col 50}Number of params =   {res}       3

{txt}{col 5}{hline 13}{c TT}{hline 60}
{col 5}     Factor  {c |} {ralign 12:Eigenvalue}   Difference        Proportion   Cumulative
{col 5}{hline 13}{c +}{hline 60}
{col 5}{ralign 11:Factor1}  {c |}{res}      1.39611      1.38147            0.9897       0.9897
{txt}{col 5}{ralign 11:Factor2}  {c |}{res}      0.01463      0.01475            0.0104       1.0001
{txt}{col 5}{ralign 11:Factor3}  {c |}{res}     -0.00011            .           -0.0001       1.0000
{txt}{col 5}{hline 13}{c BT}{hline 60}
{col 5}LR test: independent vs. saturated:  chi2({res}3{txt})  ={res} 8874.83{txt} Prob>chi2 ={res} 0.0000

{txt}Factor loadings (pattern matrix) and unique variances

{space 4}{hline 13}{c  TT}{hline 10}{hline 10}{c  TT}{hline 14}
{space 4}{space 0}{ralign 12:Variable}{space 1}{c |}{space 1}{ralign 8:Factor1}{space 1}{space 1}{ralign 8:Factor2}{space 1}{c |}{space 1}{ralign 12:Uniqueness}{space 1}
{space 4}{hline 13}{c   +}{hline 10}{hline 10}{c   +}{hline 14}
{space 4}{space 0}{ralign 12:ideothermd~f}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.4321}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.1118}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.8007}}}{space 1}
{space 4}{space 0}{ralign 12:partydifft~m}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.7810}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0212}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.3896}}}{space 1}
{space 4}{space 0}{ralign 12:diffcandth~m}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.7742}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0410}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.3989}}}{space 1}
{space 4}{hline 13}{c  BT}{hline 10}{hline 10}{c  BT}{hline 14}

{com}. 
. pwcorr ideothermdiff partydifftherm diffcandtherm if rep != .

             {txt}{c |} ideoth~f partyd~m diffca~m
{hline 13}{c +}{hline 27}
ideothermd~f {c |} {res}  1.0000 
{txt}partydifft~m {c |} {res}  0.3241   1.0000 
{txt}diffcandth~m {c |} {res}  0.3068   0.5995   1.0000 
{txt}
{com}. di (0.3241 + 0.3068 + 0.5995)/3
{res}.41013333
{txt}
{com}. 
. ****
. ** Disaggregate polarization measures
. ****
. 
. * Perceived
. reg pdiffinsure affectpol2 ideostrength2 pidstrength2 issextreme2 ///
>         sophistication2 edu2 age2 income2 female black south i.year, beta

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     4,387
{txt}{hline 13}{c +}{hline 34}   F(16, 4370)     = {res}    70.26
{txt}       Model {c |} {res}  2968.0357        16  185.502232   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 11538.4047     4,370  2.64036721   {txt}R-squared       ={res}    0.2046
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.2017
{txt}       Total {c |} {res} 14506.4404     4,386  3.30744195   {txt}Root MSE        =   {res} 1.6249

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}    pdiffinsure{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 70}        Beta
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}affectpol2 {c |}{col 17}{res}{space 2} 1.874826{col 29}{space 2} .1360357{col 40}{space 1}   13.78{col 49}{space 3}0.000{col 70}{space 3} .2226243
{txt}{space 2}ideostrength2 {c |}{col 17}{res}{space 2}  .141526{col 29}{space 2} .0899847{col 40}{space 1}    1.57{col 49}{space 3}0.116{col 70}{space 3}  .022698
{txt}{space 3}pidstrength2 {c |}{col 17}{res}{space 2} .2304148{col 29}{space 2} .0909591{col 40}{space 1}    2.53{col 49}{space 3}0.011{col 70}{space 3} .0380542
{txt}{space 4}issextreme2 {c |}{col 17}{res}{space 2}   .61188{col 29}{space 2} .1018747{col 40}{space 1}    6.01{col 49}{space 3}0.000{col 70}{space 3} .0865369
{txt}sophistication2 {c |}{col 17}{res}{space 2} .7550908{col 29}{space 2} .1303505{col 40}{space 1}    5.79{col 49}{space 3}0.000{col 70}{space 3} .0876346
{txt}{space 11}edu2 {c |}{col 17}{res}{space 2} .7895324{col 29}{space 2} .0998488{col 40}{space 1}    7.91{col 49}{space 3}0.000{col 70}{space 3} .1214053
{txt}{space 11}age2 {c |}{col 17}{res}{space 2} .1946765{col 29}{space 2} .1326588{col 40}{space 1}    1.47{col 49}{space 3}0.142{col 70}{space 3} .0209215
{txt}{space 8}income2 {c |}{col 17}{res}{space 2}  .352537{col 29}{space 2}  .099077{col 40}{space 1}    3.56{col 49}{space 3}0.000{col 70}{space 3} .0535803
{txt}{space 9}female {c |}{col 17}{res}{space 2}-.0376526{col 29}{space 2} .0502516{col 40}{space 1}   -0.75{col 49}{space 3}0.454{col 70}{space 3}-.0103466
{txt}{space 10}black {c |}{col 17}{res}{space 2} .2196522{col 29}{space 2} .0791288{col 40}{space 1}    2.78{col 49}{space 3}0.006{col 70}{space 3} .0405831
{txt}{space 10}south {c |}{col 17}{res}{space 2} -.034334{col 29}{space 2} .0531555{col 40}{space 1}   -0.65{col 49}{space 3}0.518{col 70}{space 3}-.0089549
{txt}{space 15} {c |}
{space 11}year {c |}
{space 10}1976  {c |}{col 17}{res}{space 2} .4025068{col 29}{space 2} .1038913{col 40}{space 1}    3.87{col 49}{space 3}0.000{col 70}{space 3} .0799632
{txt}{space 10}1978  {c |}{col 17}{res}{space 2} .2151486{col 29}{space 2} .1023959{col 40}{space 1}    2.10{col 49}{space 3}0.036{col 70}{space 3} .0454405
{txt}{space 10}1988  {c |}{col 17}{res}{space 2} .6167533{col 29}{space 2} .1051844{col 40}{space 1}    5.86{col 49}{space 3}0.000{col 70}{space 3} .1209516
{txt}{space 10}1994  {c |}{col 17}{res}{space 2} 1.003697{col 29}{space 2} .1022127{col 40}{space 1}    9.82{col 49}{space 3}0.000{col 70}{space 3} .2182525
{txt}{space 10}2012  {c |}{col 17}{res}{space 2} 1.325588{col 29}{space 2} .0995242{col 40}{space 1}   13.32{col 49}{space 3}0.000{col 70}{space 3}  .308045
{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2}-.1594282{col 29}{space 2} .1402189{col 40}{space 1}   -1.14{col 49}{space 3}0.256{col 70}{space 3}        .
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.         
. reg pdiffdefense affectpol2 ideostrength2 pidstrength2 issextreme2 ///
>         sophistication2 edu2 age2 income2 female black south i.year, beta

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     7,412
{txt}{hline 13}{c +}{hline 34}   F(20, 7391)     = {res}    51.74
{txt}       Model {c |} {res} 1904.03004        20  95.2015022   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 13599.4275     7,391   1.8399983   {txt}R-squared       ={res}    0.1228
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.1204
{txt}       Total {c |} {res} 15503.4575     7,411  2.09195217   {txt}Root MSE        =   {res} 1.3565

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   pdiffdefense{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 70}        Beta
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}affectpol2 {c |}{col 17}{res}{space 2} 1.910846{col 29}{space 2} .0944758{col 40}{space 1}   20.23{col 49}{space 3}0.000{col 70}{space 3} .2558851
{txt}{space 2}ideostrength2 {c |}{col 17}{res}{space 2} .0448791{col 29}{space 2} .0603372{col 40}{space 1}    0.74{col 49}{space 3}0.457{col 70}{space 3} .0087271
{txt}{space 3}pidstrength2 {c |}{col 17}{res}{space 2} .0958323{col 29}{space 2} .0580522{col 40}{space 1}    1.65{col 49}{space 3}0.099{col 70}{space 3}  .019563
{txt}{space 4}issextreme2 {c |}{col 17}{res}{space 2} .4882547{col 29}{space 2} .0741741{col 40}{space 1}    6.58{col 49}{space 3}0.000{col 70}{space 3} .0758336
{txt}sophistication2 {c |}{col 17}{res}{space 2} .3168188{col 29}{space 2} .0859001{col 40}{space 1}    3.69{col 49}{space 3}0.000{col 70}{space 3} .0443859
{txt}{space 11}edu2 {c |}{col 17}{res}{space 2} .4716654{col 29}{space 2} .0657407{col 40}{space 1}    7.17{col 49}{space 3}0.000{col 70}{space 3} .0885822
{txt}{space 11}age2 {c |}{col 17}{res}{space 2}-.3817654{col 29}{space 2} .0834796{col 40}{space 1}   -4.57{col 49}{space 3}0.000{col 70}{space 3}-.0523872
{txt}{space 8}income2 {c |}{col 17}{res}{space 2} .0529741{col 29}{space 2}  .063971{col 40}{space 1}    0.83{col 49}{space 3}0.408{col 70}{space 3}  .009907
{txt}{space 9}female {c |}{col 17}{res}{space 2}-.0163413{col 29}{space 2} .0321439{col 40}{space 1}   -0.51{col 49}{space 3}0.611{col 70}{space 3}-.0056478
{txt}{space 10}black {c |}{col 17}{res}{space 2} .2999491{col 29}{space 2} .0538379{col 40}{space 1}    5.57{col 49}{space 3}0.000{col 70}{space 3} .0638919
{txt}{space 10}south {c |}{col 17}{res}{space 2}-.1104136{col 29}{space 2}  .034579{col 40}{space 1}   -3.19{col 49}{space 3}0.001{col 70}{space 3}-.0354475
{txt}{space 15} {c |}
{space 11}year {c |}
{space 10}1982  {c |}{col 17}{res}{space 2} .2712419{col 29}{space 2} .0804676{col 40}{space 1}    3.37{col 49}{space 3}0.001{col 70}{space 3} .0504879
{txt}{space 10}1984  {c |}{col 17}{res}{space 2} .3891084{col 29}{space 2} .0730673{col 40}{space 1}    5.33{col 49}{space 3}0.000{col 70}{space 3} .0884193
{txt}{space 10}1986  {c |}{col 17}{res}{space 2}  .467558{col 29}{space 2} .0707431{col 40}{space 1}    6.61{col 49}{space 3}0.000{col 70}{space 3} .1151882
{txt}{space 10}1988  {c |}{col 17}{res}{space 2} .0763869{col 29}{space 2} .0748352{col 40}{space 1}    1.02{col 49}{space 3}0.307{col 70}{space 3} .0163798
{txt}{space 10}1990  {c |}{col 17}{res}{space 2} .2320796{col 29}{space 2} .0743587{col 40}{space 1}    3.12{col 49}{space 3}0.002{col 70}{space 3} .0510784
{txt}{space 10}1992  {c |}{col 17}{res}{space 2}  .048244{col 29}{space 2} .0710916{col 40}{space 1}    0.68{col 49}{space 3}0.497{col 70}{space 3} .0116458
{txt}{space 10}1996  {c |}{col 17}{res}{space 2}-.0319023{col 29}{space 2} .0752767{col 40}{space 1}   -0.42{col 49}{space 3}0.672{col 70}{space 3}-.0068145
{txt}{space 10}2000  {c |}{col 17}{res}{space 2} .0256653{col 29}{space 2} .1124111{col 40}{space 1}    0.23{col 49}{space 3}0.819{col 70}{space 3} .0028614
{txt}{space 10}2004  {c |}{col 17}{res}{space 2}   .14186{col 29}{space 2} .0816043{col 40}{space 1}    1.74{col 49}{space 3}0.082{col 70}{space 3} .0259015
{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2} .8353914{col 29}{space 2} .0935004{col 40}{space 1}    8.93{col 49}{space 3}0.000{col 70}{space 3}        .
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.         
. reg pdiffservice affectpol2 ideostrength2 pidstrength2 issextreme2 ///
>         sophistication2 edu2 age2 income2 female black south i.year, beta

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     9,448
{txt}{hline 13}{c +}{hline 34}   F(22, 9425)     = {res}   103.86
{txt}       Model {c |} {res} 4881.80213        22  221.900097   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 20136.3143     9,425  2.13647897   {txt}R-squared       ={res}    0.1951
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.1933
{txt}       Total {c |} {res} 25018.1164     9,447  2.64826045   {txt}Root MSE        =   {res} 1.4617

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   pdiffservice{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 70}        Beta
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}affectpol2 {c |}{col 17}{res}{space 2} 2.261416{col 29}{space 2} .0890412{col 40}{space 1}   25.40{col 49}{space 3}0.000{col 70}{space 3} .2804793
{txt}{space 2}ideostrength2 {c |}{col 17}{res}{space 2}-.0390377{col 29}{space 2} .0570216{col 40}{space 1}   -0.68{col 49}{space 3}0.494{col 70}{space 3}-.0068539
{txt}{space 3}pidstrength2 {c |}{col 17}{res}{space 2} .2056145{col 29}{space 2} .0555594{col 40}{space 1}    3.70{col 49}{space 3}0.000{col 70}{space 3} .0376734
{txt}{space 4}issextreme2 {c |}{col 17}{res}{space 2} .3886327{col 29}{space 2} .0686931{col 40}{space 1}    5.66{col 49}{space 3}0.000{col 70}{space 3} .0553078
{txt}sophistication2 {c |}{col 17}{res}{space 2} .6777947{col 29}{space 2} .0827908{col 40}{space 1}    8.19{col 49}{space 3}0.000{col 70}{space 3} .0845886
{txt}{space 11}edu2 {c |}{col 17}{res}{space 2} .9664147{col 29}{space 2} .0623852{col 40}{space 1}   15.49{col 49}{space 3}0.000{col 70}{space 3} .1614729
{txt}{space 11}age2 {c |}{col 17}{res}{space 2}-.0149039{col 29}{space 2}  .079239{col 40}{space 1}   -0.19{col 49}{space 3}0.851{col 70}{space 3}-.0018219
{txt}{space 8}income2 {c |}{col 17}{res}{space 2} .2290211{col 29}{space 2} .0605631{col 40}{space 1}    3.78{col 49}{space 3}0.000{col 70}{space 3} .0385336
{txt}{space 9}female {c |}{col 17}{res}{space 2} -.004136{col 29}{space 2} .0306029{col 40}{space 1}   -0.14{col 49}{space 3}0.892{col 70}{space 3}-.0012708
{txt}{space 10}black {c |}{col 17}{res}{space 2} .3938022{col 29}{space 2} .0494967{col 40}{space 1}    7.96{col 49}{space 3}0.000{col 70}{space 3} .0784688
{txt}{space 10}south {c |}{col 17}{res}{space 2}-.1009387{col 29}{space 2} .0328202{col 40}{space 1}   -3.08{col 49}{space 3}0.002{col 70}{space 3}-.0291005
{txt}{space 15} {c |}
{space 11}year {c |}
{space 10}1984  {c |}{col 17}{res}{space 2}  .042866{col 29}{space 2} .0776719{col 40}{space 1}    0.55{col 49}{space 3}0.581{col 70}{space 3} .0078587
{txt}{space 10}1986  {c |}{col 17}{res}{space 2}-.1112842{col 29}{space 2} .0755616{col 40}{space 1}   -1.47{col 49}{space 3}0.141{col 70}{space 3}-.0217688
{txt}{space 10}1988  {c |}{col 17}{res}{space 2}-.5102995{col 29}{space 2} .0803141{col 40}{space 1}   -6.35{col 49}{space 3}0.000{col 70}{space 3}-.0867062
{txt}{space 10}1990  {c |}{col 17}{res}{space 2}-.4957489{col 29}{space 2} .0794461{col 40}{space 1}   -6.24{col 49}{space 3}0.000{col 70}{space 3}-.0862865
{txt}{space 10}1992  {c |}{col 17}{res}{space 2}-.1962641{col 29}{space 2} .0760035{col 40}{space 1}   -2.58{col 49}{space 3}0.010{col 70}{space 3}-.0380964
{txt}{space 10}1994  {c |}{col 17}{res}{space 2}-.3050952{col 29}{space 2} .0791398{col 40}{space 1}   -3.86{col 49}{space 3}0.000{col 70}{space 3}-.0535046
{txt}{space 10}1996  {c |}{col 17}{res}{space 2}-.1319829{col 29}{space 2}  .079999{col 40}{space 1}   -1.65{col 49}{space 3}0.099{col 70}{space 3}-.0226948
{txt}{space 10}1998  {c |}{col 17}{res}{space 2}-.1391434{col 29}{space 2} .0823159{col 40}{space 1}   -1.69{col 49}{space 3}0.091{col 70}{space 3}-.0225278
{txt}{space 10}2000  {c |}{col 17}{res}{space 2}-.0565932{col 29}{space 2} .1177183{col 40}{space 1}   -0.48{col 49}{space 3}0.631{col 70}{space 3}-.0051508
{txt}{space 10}2004  {c |}{col 17}{res}{space 2}-.1907338{col 29}{space 2} .0876103{col 40}{space 1}   -2.18{col 49}{space 3}0.030{col 70}{space 3}-.0276311
{txt}{space 10}2012  {c |}{col 17}{res}{space 2} .1888694{col 29}{space 2} .0772693{col 40}{space 1}    2.44{col 49}{space 3}0.015{col 70}{space 3}  .036388
{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2} .7406144{col 29}{space 2} .0918907{col 40}{space 1}    8.06{col 49}{space 3}0.000{col 70}{space 3}        .
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.         
. reg pdiffaid affectpol2 ideostrength2 pidstrength2 issextreme2 ///
>         sophistication2 edu2 age2 income2 female black south i.year, beta

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     8,066
{txt}{hline 13}{c +}{hline 34}   F(21, 8044)     = {res}    92.02
{txt}       Model {c |} {res} 3934.93794        21  187.377997   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 16379.9289     8,044  2.03629151   {txt}R-squared       ={res}    0.1937
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.1916
{txt}       Total {c |} {res} 20314.8668     8,065  2.51889236   {txt}Root MSE        =   {res}  1.427

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       pdiffaid{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 70}        Beta
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}affectpol2 {c |}{col 17}{res}{space 2} 1.964153{col 29}{space 2} .0893453{col 40}{space 1}   21.98{col 49}{space 3}0.000{col 70}{space 3}  .252528
{txt}{space 2}ideostrength2 {c |}{col 17}{res}{space 2} .2246411{col 29}{space 2} .0599339{col 40}{space 1}    3.75{col 49}{space 3}0.000{col 70}{space 3} .0402904
{txt}{space 3}pidstrength2 {c |}{col 17}{res}{space 2} .1689516{col 29}{space 2} .0587775{col 40}{space 1}    2.87{col 49}{space 3}0.004{col 70}{space 3}  .031172
{txt}{space 4}issextreme2 {c |}{col 17}{res}{space 2}  .447594{col 29}{space 2} .0674175{col 40}{space 1}    6.64{col 49}{space 3}0.000{col 70}{space 3} .0712495
{txt}sophistication2 {c |}{col 17}{res}{space 2} .6366348{col 29}{space 2} .0852476{col 40}{space 1}    7.47{col 49}{space 3}0.000{col 70}{space 3} .0826811
{txt}{space 11}edu2 {c |}{col 17}{res}{space 2} .8255602{col 29}{space 2} .0660603{col 40}{space 1}   12.50{col 49}{space 3}0.000{col 70}{space 3} .1431206
{txt}{space 11}age2 {c |}{col 17}{res}{space 2} .3125898{col 29}{space 2} .0854621{col 40}{space 1}    3.66{col 49}{space 3}0.000{col 70}{space 3} .0386727
{txt}{space 8}income2 {c |}{col 17}{res}{space 2}  .080774{col 29}{space 2} .0638947{col 40}{space 1}    1.26{col 49}{space 3}0.206{col 70}{space 3} .0138291
{txt}{space 9}female {c |}{col 17}{res}{space 2} .0286525{col 29}{space 2} .0324416{col 40}{space 1}    0.88{col 49}{space 3}0.377{col 70}{space 3} .0090241
{txt}{space 10}black {c |}{col 17}{res}{space 2} .6357298{col 29}{space 2} .0554489{col 40}{space 1}   11.47{col 49}{space 3}0.000{col 70}{space 3} .1204663
{txt}{space 10}south {c |}{col 17}{res}{space 2}-.0563456{col 29}{space 2} .0348514{col 40}{space 1}   -1.62{col 49}{space 3}0.106{col 70}{space 3}-.0165067
{txt}{space 15} {c |}
{space 11}year {c |}
{space 10}1976  {c |}{col 17}{res}{space 2} .2751449{col 29}{space 2} .0666609{col 40}{space 1}    4.13{col 49}{space 3}0.000{col 70}{space 3} .0527603
{txt}{space 10}1978  {c |}{col 17}{res}{space 2} .1627343{col 29}{space 2} .0650716{col 40}{space 1}    2.50{col 49}{space 3}0.012{col 70}{space 3} .0331441
{txt}{space 10}1980  {c |}{col 17}{res}{space 2} .9371602{col 29}{space 2} .0751914{col 40}{space 1}   12.46{col 49}{space 3}0.000{col 70}{space 3} .1507168
{txt}{space 10}1982  {c |}{col 17}{res}{space 2} .8479472{col 29}{space 2}  .075362{col 40}{space 1}   11.25{col 49}{space 3}0.000{col 70}{space 3} .1373686
{txt}{space 10}1984  {c |}{col 17}{res}{space 2} .8081228{col 29}{space 2} .0653687{col 40}{space 1}   12.36{col 49}{space 3}0.000{col 70}{space 3} .1622526
{txt}{space 10}1988  {c |}{col 17}{res}{space 2} .3117434{col 29}{space 2} .0685884{col 40}{space 1}    4.55{col 49}{space 3}0.000{col 70}{space 3} .0575213
{txt}{space 10}1990  {c |}{col 17}{res}{space 2} .5896559{col 29}{space 2} .0680182{col 40}{space 1}    8.67{col 49}{space 3}0.000{col 70}{space 3} .1131292
{txt}{space 10}1994  {c |}{col 17}{res}{space 2} .5295731{col 29}{space 2} .0677853{col 40}{space 1}    7.81{col 49}{space 3}0.000{col 70}{space 3} .1019781
{txt}{space 10}2000  {c |}{col 17}{res}{space 2} .6006778{col 29}{space 2} .1136784{col 40}{space 1}    5.28{col 49}{space 3}0.000{col 70}{space 3} .0575503
{txt}{space 10}2004  {c |}{col 17}{res}{space 2} .6713511{col 29}{space 2}  .077591{col 40}{space 1}    8.65{col 49}{space 3}0.000{col 70}{space 3} .1045384
{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2}-.3748425{col 29}{space 2} .0847287{col 40}{space 1}   -4.42{col 49}{space 3}0.000{col 70}{space 3}        .
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.         
. reg pdiffjobs affectpol2 ideostrength2 pidstrength2 issextreme2 ///
>         sophistication2 edu2 age2 income2 female black south i.year, beta       

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     9,142
{txt}{hline 13}{c +}{hline 34}   F(22, 9119)     = {res}    95.27
{txt}       Model {c |} {res} 4856.72293        22  220.760133   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 21131.3344     9,119  2.31728637   {txt}R-squared       ={res}    0.1869
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.1849
{txt}       Total {c |} {res} 25988.0573     9,141  2.84302126   {txt}Root MSE        =   {res} 1.5223

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      pdiffjobs{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 70}        Beta
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}affectpol2 {c |}{col 17}{res}{space 2} 2.078268{col 29}{space 2} .0906884{col 40}{space 1}   22.92{col 49}{space 3}0.000{col 70}{space 3} .2553361
{txt}{space 2}ideostrength2 {c |}{col 17}{res}{space 2} .0601781{col 29}{space 2} .0595411{col 40}{space 1}    1.01{col 49}{space 3}0.312{col 70}{space 3} .0102367
{txt}{space 3}pidstrength2 {c |}{col 17}{res}{space 2} .2613511{col 29}{space 2} .0584756{col 40}{space 1}    4.47{col 49}{space 3}0.000{col 70}{space 3}  .046197
{txt}{space 4}issextreme2 {c |}{col 17}{res}{space 2} .5182514{col 29}{space 2} .0682579{col 40}{space 1}    7.59{col 49}{space 3}0.000{col 70}{space 3} .0765277
{txt}sophistication2 {c |}{col 17}{res}{space 2} .6485369{col 29}{space 2}  .085128{col 40}{space 1}    7.62{col 49}{space 3}0.000{col 70}{space 3} .0796717
{txt}{space 11}edu2 {c |}{col 17}{res}{space 2} .8176014{col 29}{space 2} .0660637{col 40}{space 1}   12.38{col 49}{space 3}0.000{col 70}{space 3} .1334628
{txt}{space 11}age2 {c |}{col 17}{res}{space 2} .1995233{col 29}{space 2} .0852044{col 40}{space 1}    2.34{col 49}{space 3}0.019{col 70}{space 3} .0232881
{txt}{space 8}income2 {c |}{col 17}{res}{space 2}  .163637{col 29}{space 2} .0637331{col 40}{space 1}    2.57{col 49}{space 3}0.010{col 70}{space 3} .0266791
{txt}{space 9}female {c |}{col 17}{res}{space 2}-.0492897{col 29}{space 2}  .032426{col 40}{space 1}   -1.52{col 49}{space 3}0.129{col 70}{space 3} -.014613
{txt}{space 10}black {c |}{col 17}{res}{space 2} .4459033{col 29}{space 2} .0543847{col 40}{space 1}    8.20{col 49}{space 3}0.000{col 70}{space 3} .0824378
{txt}{space 10}south {c |}{col 17}{res}{space 2} -.090871{col 29}{space 2} .0346804{col 40}{space 1}   -2.62{col 49}{space 3}0.009{col 70}{space 3}-.0252719
{txt}{space 15} {c |}
{space 11}year {c |}
{space 10}1976  {c |}{col 17}{res}{space 2} .1290766{col 29}{space 2}  .071124{col 40}{space 1}    1.81{col 49}{space 3}0.070{col 70}{space 3} .0221968
{txt}{space 10}1978  {c |}{col 17}{res}{space 2}-.0971376{col 29}{space 2} .0704197{col 40}{space 1}   -1.38{col 49}{space 3}0.168{col 70}{space 3}-.0173158
{txt}{space 10}1980  {c |}{col 17}{res}{space 2} .3147414{col 29}{space 2} .0820784{col 40}{space 1}    3.83{col 49}{space 3}0.000{col 70}{space 3} .0437022
{txt}{space 10}1982  {c |}{col 17}{res}{space 2}  .449851{col 29}{space 2} .0798999{col 40}{space 1}    5.63{col 49}{space 3}0.000{col 70}{space 3} .0655055
{txt}{space 10}1984  {c |}{col 17}{res}{space 2} .0266571{col 29}{space 2} .0705843{col 40}{space 1}    0.38{col 49}{space 3}0.706{col 70}{space 3} .0047032
{txt}{space 10}1988  {c |}{col 17}{res}{space 2} .0004186{col 29}{space 2}  .074924{col 40}{space 1}    0.01{col 49}{space 3}0.996{col 70}{space 3} .0000666
{txt}{space 10}1992  {c |}{col 17}{res}{space 2} .3010625{col 29}{space 2} .0689397{col 40}{space 1}    4.37{col 49}{space 3}0.000{col 70}{space 3} .0552161
{txt}{space 10}1994  {c |}{col 17}{res}{space 2} .3990385{col 29}{space 2} .0720189{col 40}{space 1}    5.54{col 49}{space 3}0.000{col 70}{space 3} .0692711
{txt}{space 10}2000  {c |}{col 17}{res}{space 2}  .264966{col 29}{space 2} .1191753{col 40}{space 1}    2.22{col 49}{space 3}0.026{col 70}{space 3} .0229325
{txt}{space 10}2004  {c |}{col 17}{res}{space 2} .3603672{col 29}{space 2} .0819053{col 40}{space 1}    4.40{col 49}{space 3}0.000{col 70}{space 3} .0507371
{txt}{space 10}2012  {c |}{col 17}{res}{space 2} .7890901{col 29}{space 2} .0690515{col 40}{space 1}   11.43{col 49}{space 3}0.000{col 70}{space 3} .1477283
{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2} .1492293{col 29}{space 2} .0859963{col 40}{space 1}    1.74{col 49}{space 3}0.083{col 70}{space 3}        .
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. reg partyideodiff affectpol2 ideostrength2 pidstrength2 issextreme2 ///
>         sophistication2 edu2 age2 income2 female black south i.year, beta       

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}    14,897
{txt}{hline 13}{c +}{hline 34}   F(28, 14868)    = {res}   102.18
{txt}       Model {c |} {res} 5585.48008        28  199.481431   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 29025.3135    14,868  1.95220026   {txt}R-squared       ={res}    0.1614
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.1598
{txt}       Total {c |} {res} 34610.7936    14,896  2.32349581   {txt}Root MSE        =   {res} 1.3972

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}  partyideodiff{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 70}        Beta
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}affectpol2 {c |}{col 17}{res}{space 2} 1.708294{col 29}{space 2} .0658182{col 40}{space 1}   25.95{col 49}{space 3}0.000{col 70}{space 3}  .229969
{txt}{space 2}ideostrength2 {c |}{col 17}{res}{space 2}  .122041{col 29}{space 2} .0430595{col 40}{space 1}    2.83{col 49}{space 3}0.005{col 70}{space 3} .0228955
{txt}{space 3}pidstrength2 {c |}{col 17}{res}{space 2} .3087677{col 29}{space 2}  .042024{col 40}{space 1}    7.35{col 49}{space 3}0.000{col 70}{space 3} .0604597
{txt}{space 4}issextreme2 {c |}{col 17}{res}{space 2}-.0388658{col 29}{space 2} .0483948{col 40}{space 1}   -0.80{col 49}{space 3}0.422{col 70}{space 3}-.0064107
{txt}sophistication2 {c |}{col 17}{res}{space 2} .3482239{col 29}{space 2} .0621233{col 40}{space 1}    5.61{col 49}{space 3}0.000{col 70}{space 3} .0472275
{txt}{space 11}edu2 {c |}{col 17}{res}{space 2} .6637398{col 29}{space 2} .0473137{col 40}{space 1}   14.03{col 49}{space 3}0.000{col 70}{space 3} .1201808
{txt}{space 11}age2 {c |}{col 17}{res}{space 2} .0555105{col 29}{space 2}  .059783{col 40}{space 1}    0.93{col 49}{space 3}0.353{col 70}{space 3} .0073308
{txt}{space 8}income2 {c |}{col 17}{res}{space 2} .2335798{col 29}{space 2} .0458003{col 40}{space 1}    5.10{col 49}{space 3}0.000{col 70}{space 3} .0420845
{txt}{space 9}female {c |}{col 17}{res}{space 2}-.0140444{col 29}{space 2} .0232566{col 40}{space 1}   -0.60{col 49}{space 3}0.546{col 70}{space 3}-.0046067
{txt}{space 10}black {c |}{col 17}{res}{space 2} .0713481{col 29}{space 2} .0389255{col 40}{space 1}    1.83{col 49}{space 3}0.067{col 70}{space 3} .0145883
{txt}{space 10}south {c |}{col 17}{res}{space 2}-.0382184{col 29}{space 2} .0249023{col 40}{space 1}   -1.53{col 49}{space 3}0.125{col 70}{space 3}-.0117948
{txt}{space 15} {c |}
{space 11}year {c |}
{space 10}1976  {c |}{col 17}{res}{space 2} .4047384{col 29}{space 2} .0617595{col 40}{space 1}    6.55{col 49}{space 3}0.000{col 70}{space 3} .0641442
{txt}{space 10}1978  {c |}{col 17}{res}{space 2}  .098606{col 29}{space 2} .0604046{col 40}{space 1}    1.63{col 49}{space 3}0.103{col 70}{space 3} .0164634
{txt}{space 10}1980  {c |}{col 17}{res}{space 2} .4170575{col 29}{space 2} .0697756{col 40}{space 1}    5.98{col 49}{space 3}0.000{col 70}{space 3} .0547298
{txt}{space 10}1982  {c |}{col 17}{res}{space 2} .6456488{col 29}{space 2} .0696528{col 40}{space 1}    9.27{col 49}{space 3}0.000{col 70}{space 3} .0855693
{txt}{space 10}1984  {c |}{col 17}{res}{space 2} .5555604{col 29}{space 2} .0610736{col 40}{space 1}    9.10{col 49}{space 3}0.000{col 70}{space 3} .0905282
{txt}{space 10}1986  {c |}{col 17}{res}{space 2} .3575111{col 29}{space 2} .0589142{col 40}{space 1}    6.07{col 49}{space 3}0.000{col 70}{space 3} .0627015
{txt}{space 10}1988  {c |}{col 17}{res}{space 2} .5677252{col 29}{space 2} .0639523{col 40}{space 1}    8.88{col 49}{space 3}0.000{col 70}{space 3} .0853355
{txt}{space 10}1990  {c |}{col 17}{res}{space 2} .4047218{col 29}{space 2} .0624366{col 40}{space 1}    6.48{col 49}{space 3}0.000{col 70}{space 3} .0642384
{txt}{space 10}1992  {c |}{col 17}{res}{space 2} .6483202{col 29}{space 2}  .058575{col 40}{space 1}   11.07{col 49}{space 3}0.000{col 70}{space 3} .1137046
{txt}{space 10}1994  {c |}{col 17}{res}{space 2} .5254848{col 29}{space 2} .0630685{col 40}{space 1}    8.33{col 49}{space 3}0.000{col 70}{space 3} .0818812
{txt}{space 10}1996  {c |}{col 17}{res}{space 2} .5770314{col 29}{space 2} .0637206{col 40}{space 1}    9.06{col 49}{space 3}0.000{col 70}{space 3} .0887741
{txt}{space 10}1998  {c |}{col 17}{res}{space 2} .5228386{col 29}{space 2} .0668575{col 40}{space 1}    7.82{col 49}{space 3}0.000{col 70}{space 3} .0746224
{txt}{space 10}2000  {c |}{col 17}{res}{space 2} .7859797{col 29}{space 2} .1050323{col 40}{space 1}    7.48{col 49}{space 3}0.000{col 70}{space 3} .0610747
{txt}{space 10}2004  {c |}{col 17}{res}{space 2} .8250509{col 29}{space 2} .0728037{col 40}{space 1}   11.33{col 49}{space 3}0.000{col 70}{space 3} .1026013
{txt}{space 10}2008  {c |}{col 17}{res}{space 2} .8535508{col 29}{space 2} .0751805{col 40}{space 1}   11.35{col 49}{space 3}0.000{col 70}{space 3}  .101243
{txt}{space 10}2012  {c |}{col 17}{res}{space 2} 1.128999{col 29}{space 2} .0606161{col 40}{space 1}   18.63{col 49}{space 3}0.000{col 70}{space 3} .1890028
{txt}{space 10}2016  {c |}{col 17}{res}{space 2} .9728912{col 29}{space 2} .0699596{col 40}{space 1}   13.91{col 49}{space 3}0.000{col 70}{space 3} .1292302
{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2} .8355079{col 29}{space 2} .0653405{col 40}{space 1}   12.79{col 49}{space 3}0.000{col 70}{space 3}        .
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
.         
. reg perceivepol2 ideothermdiff2 ideostrength2 pidstrength2 issextreme2 ///
>         sophistication2 edu2 age2 income2 female black south i.year, beta       

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}    13,902
{txt}{hline 13}{c +}{hline 34}   F(27, 13874)    = {res}   146.79
{txt}       Model {c |} {res} 154.268164        27  5.71363572   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res}  540.03943    13,874  .038924566   {txt}R-squared       ={res}    0.2222
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.2207
{txt}       Total {c |} {res} 694.307594    13,901  .049946593   {txt}Root MSE        =   {res} .19729

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   perceivepol2{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 70}        Beta
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}ideothermdiff2 {c |}{col 17}{res}{space 2} .1683601{col 29}{space 2} .0082864{col 40}{space 1}   20.32{col 49}{space 3}0.000{col 70}{space 3} .1687152
{txt}{space 2}ideostrength2 {c |}{col 17}{res}{space 2} .0259727{col 29}{space 2} .0064892{col 40}{space 1}    4.00{col 49}{space 3}0.000{col 70}{space 3} .0332045
{txt}{space 3}pidstrength2 {c |}{col 17}{res}{space 2} .0876297{col 29}{space 2} .0059129{col 40}{space 1}   14.82{col 49}{space 3}0.000{col 70}{space 3}  .117143
{txt}{space 4}issextreme2 {c |}{col 17}{res}{space 2} .0670102{col 29}{space 2}  .007113{col 40}{space 1}    9.42{col 49}{space 3}0.000{col 70}{space 3} .0744189
{txt}sophistication2 {c |}{col 17}{res}{space 2} .1180852{col 29}{space 2} .0090774{col 40}{space 1}   13.01{col 49}{space 3}0.000{col 70}{space 3} .1087108
{txt}{space 11}edu2 {c |}{col 17}{res}{space 2} .1174722{col 29}{space 2} .0069662{col 40}{space 1}   16.86{col 49}{space 3}0.000{col 70}{space 3} .1435999
{txt}{space 11}age2 {c |}{col 17}{res}{space 2} .0092314{col 29}{space 2}  .008784{col 40}{space 1}    1.05{col 49}{space 3}0.293{col 70}{space 3}  .008258
{txt}{space 8}income2 {c |}{col 17}{res}{space 2} .0289196{col 29}{space 2} .0067316{col 40}{space 1}    4.30{col 49}{space 3}0.000{col 70}{space 3} .0351779
{txt}{space 9}female {c |}{col 17}{res}{space 2} -.001169{col 29}{space 2} .0033962{col 40}{space 1}   -0.34{col 49}{space 3}0.731{col 70}{space 3}-.0026149
{txt}{space 10}black {c |}{col 17}{res}{space 2} .0563602{col 29}{space 2} .0056803{col 40}{space 1}    9.92{col 49}{space 3}0.000{col 70}{space 3} .0786774
{txt}{space 10}south {c |}{col 17}{res}{space 2}-.0132981{col 29}{space 2} .0036449{col 40}{space 1}   -3.65{col 49}{space 3}0.000{col 70}{space 3}-.0279557
{txt}{space 15} {c |}
{space 11}year {c |}
{space 10}1976  {c |}{col 17}{res}{space 2} .0269716{col 29}{space 2} .0087458{col 40}{space 1}    3.08{col 49}{space 3}0.002{col 70}{space 3} .0298809
{txt}{space 10}1980  {c |}{col 17}{res}{space 2} .0559464{col 29}{space 2} .0098107{col 40}{space 1}    5.70{col 49}{space 3}0.000{col 70}{space 3} .0520317
{txt}{space 10}1982  {c |}{col 17}{res}{space 2} .0777676{col 29}{space 2} .0097859{col 40}{space 1}    7.95{col 49}{space 3}0.000{col 70}{space 3} .0730337
{txt}{space 10}1984  {c |}{col 17}{res}{space 2} .0864296{col 29}{space 2} .0086387{col 40}{space 1}   10.00{col 49}{space 3}0.000{col 70}{space 3} .0990445
{txt}{space 10}1986  {c |}{col 17}{res}{space 2} .0833415{col 29}{space 2} .0083028{col 40}{space 1}   10.04{col 49}{space 3}0.000{col 70}{space 3} .1030109
{txt}{space 10}1988  {c |}{col 17}{res}{space 2} .0422855{col 29}{space 2} .0089681{col 40}{space 1}    4.72{col 49}{space 3}0.000{col 70}{space 3} .0452592
{txt}{space 10}1990  {c |}{col 17}{res}{space 2} .0391378{col 29}{space 2} .0087763{col 40}{space 1}    4.46{col 49}{space 3}0.000{col 70}{space 3} .0438857
{txt}{space 10}1992  {c |}{col 17}{res}{space 2} .0774875{col 29}{space 2} .0082161{col 40}{space 1}    9.43{col 49}{space 3}0.000{col 70}{space 3} .0966724
{txt}{space 10}1994  {c |}{col 17}{res}{space 2} .0753718{col 29}{space 2} .0088387{col 40}{space 1}    8.53{col 49}{space 3}0.000{col 70}{space 3} .0835444
{txt}{space 10}1996  {c |}{col 17}{res}{space 2} .0847358{col 29}{space 2} .0090016{col 40}{space 1}    9.41{col 49}{space 3}0.000{col 70}{space 3} .0918862
{txt}{space 10}1998  {c |}{col 17}{res}{space 2} .1021189{col 29}{space 2} .0094882{col 40}{space 1}   10.76{col 49}{space 3}0.000{col 70}{space 3} .1018586
{txt}{space 10}2000  {c |}{col 17}{res}{space 2} .0794205{col 29}{space 2} .0147458{col 40}{space 1}    5.39{col 49}{space 3}0.000{col 70}{space 3} .0438522
{txt}{space 10}2004  {c |}{col 17}{res}{space 2} .0950897{col 29}{space 2} .0102472{col 40}{space 1}    9.28{col 49}{space 3}0.000{col 70}{space 3} .0838754
{txt}{space 10}2008  {c |}{col 17}{res}{space 2} .1943071{col 29}{space 2}  .010808{col 40}{space 1}   17.98{col 49}{space 3}0.000{col 70}{space 3} .1589055
{txt}{space 10}2012  {c |}{col 17}{res}{space 2} .2028705{col 29}{space 2} .0085581{col 40}{space 1}   23.71{col 49}{space 3}0.000{col 70}{space 3} .2395596
{txt}{space 10}2016  {c |}{col 17}{res}{space 2} .2193496{col 29}{space 2} .0099232{col 40}{space 1}   22.10{col 49}{space 3}0.000{col 70}{space 3} .2041553
{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2} .0633727{col 29}{space 2} .0094002{col 40}{space 1}    6.74{col 49}{space 3}0.000{col 70}{space 3}        .
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. reg perceivepol2 partydifftherm2 ideostrength2 pidstrength2 issextreme2 ///
>         sophistication2 edu2 age2 income2 female black south i.year, beta       

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}    13,275
{txt}{hline 13}{c +}{hline 34}   F(26, 13248)    = {res}   182.27
{txt}       Model {c |} {res} 178.401536        26  6.86159753   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 498.732788    13,248  .037645893   {txt}R-squared       ={res}    0.2635
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.2620
{txt}       Total {c |} {res} 677.134324    13,274  .051012078   {txt}Root MSE        =   {res} .19403

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   perceivepol2{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 70}        Beta
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
partydifftherm2 {c |}{col 17}{res}{space 2} .2481202{col 29}{space 2} .0078462{col 40}{space 1}   31.62{col 49}{space 3}0.000{col 70}{space 3} .2794912
{txt}{space 2}ideostrength2 {c |}{col 17}{res}{space 2} .0362462{col 29}{space 2} .0061804{col 40}{space 1}    5.86{col 49}{space 3}0.000{col 70}{space 3} .0460557
{txt}{space 3}pidstrength2 {c |}{col 17}{res}{space 2}  .019598{col 29}{space 2} .0064203{col 40}{space 1}    3.05{col 49}{space 3}0.002{col 70}{space 3} .0260726
{txt}{space 4}issextreme2 {c |}{col 17}{res}{space 2} .0484186{col 29}{space 2} .0073088{col 40}{space 1}    6.62{col 49}{space 3}0.000{col 70}{space 3} .0520105
{txt}sophistication2 {c |}{col 17}{res}{space 2} .1045181{col 29}{space 2} .0091568{col 40}{space 1}   11.41{col 49}{space 3}0.000{col 70}{space 3} .0950433
{txt}{space 11}edu2 {c |}{col 17}{res}{space 2} .1419937{col 29}{space 2} .0070127{col 40}{space 1}   20.25{col 49}{space 3}0.000{col 70}{space 3} .1713127
{txt}{space 11}age2 {c |}{col 17}{res}{space 2}-.0002587{col 29}{space 2} .0087464{col 40}{space 1}   -0.03{col 49}{space 3}0.976{col 70}{space 3}-.0002313
{txt}{space 8}income2 {c |}{col 17}{res}{space 2} .0403163{col 29}{space 2} .0067483{col 40}{space 1}    5.97{col 49}{space 3}0.000{col 70}{space 3} .0490713
{txt}{space 9}female {c |}{col 17}{res}{space 2}-.0034834{col 29}{space 2}  .003425{col 40}{space 1}   -1.02{col 49}{space 3}0.309{col 70}{space 3}-.0077104
{txt}{space 10}black {c |}{col 17}{res}{space 2} .0302866{col 29}{space 2} .0056291{col 40}{space 1}    5.38{col 49}{space 3}0.000{col 70}{space 3} .0427489
{txt}{space 10}south {c |}{col 17}{res}{space 2}-.0082689{col 29}{space 2} .0036457{col 40}{space 1}   -2.27{col 49}{space 3}0.023{col 70}{space 3}-.0173007
{txt}{space 15} {c |}
{space 11}year {c |}
{space 10}1980  {c |}{col 17}{res}{space 2} .0739172{col 29}{space 2} .0095451{col 40}{space 1}    7.74{col 49}{space 3}0.000{col 70}{space 3} .0713427
{txt}{space 10}1982  {c |}{col 17}{res}{space 2} .0869076{col 29}{space 2}  .009549{col 40}{space 1}    9.10{col 49}{space 3}0.000{col 70}{space 3} .0842388
{txt}{space 10}1984  {c |}{col 17}{res}{space 2} .0840817{col 29}{space 2} .0085248{col 40}{space 1}    9.86{col 49}{space 3}0.000{col 70}{space 3} .0986606
{txt}{space 10}1986  {c |}{col 17}{res}{space 2} .0912836{col 29}{space 2} .0081851{col 40}{space 1}   11.15{col 49}{space 3}0.000{col 70}{space 3} .1153295
{txt}{space 10}1988  {c |}{col 17}{res}{space 2} .0428982{col 29}{space 2} .0088287{col 40}{space 1}    4.86{col 49}{space 3}0.000{col 70}{space 3} .0471552
{txt}{space 10}1990  {c |}{col 17}{res}{space 2}  .056053{col 29}{space 2} .0086232{col 40}{space 1}    6.50{col 49}{space 3}0.000{col 70}{space 3} .0641285
{txt}{space 10}1992  {c |}{col 17}{res}{space 2} .0821358{col 29}{space 2} .0081586{col 40}{space 1}   10.07{col 49}{space 3}0.000{col 70}{space 3} .1043609
{txt}{space 10}1994  {c |}{col 17}{res}{space 2} .0848936{col 29}{space 2} .0086603{col 40}{space 1}    9.80{col 49}{space 3}0.000{col 70}{space 3} .0966063
{txt}{space 10}1996  {c |}{col 17}{res}{space 2} .0810473{col 29}{space 2} .0088585{col 40}{space 1}    9.15{col 49}{space 3}0.000{col 70}{space 3} .0895609
{txt}{space 10}1998  {c |}{col 17}{res}{space 2} .1033433{col 29}{space 2} .0092403{col 40}{space 1}   11.18{col 49}{space 3}0.000{col 70}{space 3} .1063698
{txt}{space 10}2000  {c |}{col 17}{res}{space 2} .0767375{col 29}{space 2} .0143485{col 40}{space 1}    5.35{col 49}{space 3}0.000{col 70}{space 3} .0435697
{txt}{space 10}2004  {c |}{col 17}{res}{space 2} .0884145{col 29}{space 2} .0100888{col 40}{space 1}    8.76{col 49}{space 3}0.000{col 70}{space 3} .0798883
{txt}{space 10}2008  {c |}{col 17}{res}{space 2} .1778313{col 29}{space 2} .0106061{col 40}{space 1}   16.77{col 49}{space 3}0.000{col 70}{space 3} .1496176
{txt}{space 10}2012  {c |}{col 17}{res}{space 2} .1876039{col 29}{space 2} .0085108{col 40}{space 1}   22.04{col 49}{space 3}0.000{col 70}{space 3} .2269899
{txt}{space 10}2016  {c |}{col 17}{res}{space 2} .2207579{col 29}{space 2} .0098679{col 40}{space 1}   22.37{col 49}{space 3}0.000{col 70}{space 3} .2078219
{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2} .0612453{col 29}{space 2} .0096646{col 40}{space 1}    6.34{col 49}{space 3}0.000{col 70}{space 3}        .
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. reg perceivepol2 diffcandtherm2 ideostrength2 pidstrength2 issextreme2 ///
>         sophistication2 edu2 age2 income2 female black south i.year, beta       

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     9,883
{txt}{hline 13}{c +}{hline 34}   F(22, 9860)     = {res}   144.55
{txt}       Model {c |} {res} 128.060138        22  5.82091538   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 397.041849     9,860  .040267936   {txt}R-squared       ={res}    0.2439
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.2422
{txt}       Total {c |} {res} 525.101987     9,882  .053137218   {txt}Root MSE        =   {res} .20067

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}   perceivepol2{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 70}        Beta
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}diffcandtherm2 {c |}{col 17}{res}{space 2} .1546632{col 29}{space 2} .0081121{col 40}{space 1}   19.07{col 49}{space 3}0.000{col 70}{space 3} .1873171
{txt}{space 2}ideostrength2 {c |}{col 17}{res}{space 2}  .053713{col 29}{space 2} .0073368{col 40}{space 1}    7.32{col 49}{space 3}0.000{col 70}{space 3} .0672214
{txt}{space 3}pidstrength2 {c |}{col 17}{res}{space 2} .0671028{col 29}{space 2} .0072037{col 40}{space 1}    9.32{col 49}{space 3}0.000{col 70}{space 3} .0881737
{txt}{space 4}issextreme2 {c |}{col 17}{res}{space 2} .0567949{col 29}{space 2} .0084505{col 40}{space 1}    6.72{col 49}{space 3}0.000{col 70}{space 3} .0624757
{txt}sophistication2 {c |}{col 17}{res}{space 2} .1110016{col 29}{space 2}  .011084{col 40}{space 1}   10.01{col 49}{space 3}0.000{col 70}{space 3} .0986363
{txt}{space 11}edu2 {c |}{col 17}{res}{space 2} .1136486{col 29}{space 2} .0084122{col 40}{space 1}   13.51{col 49}{space 3}0.000{col 70}{space 3} .1363114
{txt}{space 11}age2 {c |}{col 17}{res}{space 2} .0100871{col 29}{space 2} .0104714{col 40}{space 1}    0.96{col 49}{space 3}0.335{col 70}{space 3}  .008852
{txt}{space 8}income2 {c |}{col 17}{res}{space 2} .0319245{col 29}{space 2} .0081439{col 40}{space 1}    3.92{col 49}{space 3}0.000{col 70}{space 3} .0378981
{txt}{space 9}female {c |}{col 17}{res}{space 2}-.0036346{col 29}{space 2} .0041054{col 40}{space 1}   -0.89{col 49}{space 3}0.376{col 70}{space 3}-.0078813
{txt}{space 10}black {c |}{col 17}{res}{space 2} .0498353{col 29}{space 2}   .00673{col 40}{space 1}    7.40{col 49}{space 3}0.000{col 70}{space 3} .0690116
{txt}{space 10}south {c |}{col 17}{res}{space 2}-.0051898{col 29}{space 2} .0043949{col 40}{space 1}   -1.18{col 49}{space 3}0.238{col 70}{space 3}-.0106159
{txt}{space 15} {c |}
{space 11}year {c |}
{space 10}1976  {c |}{col 17}{res}{space 2} .0350672{col 29}{space 2} .0086429{col 40}{space 1}    4.06{col 49}{space 3}0.000{col 70}{space 3} .0456953
{txt}{space 10}1980  {c |}{col 17}{res}{space 2}  .061472{col 29}{space 2} .0097329{col 40}{space 1}    6.32{col 49}{space 3}0.000{col 70}{space 3} .0670423
{txt}{space 10}1984  {c |}{col 17}{res}{space 2} .0771754{col 29}{space 2} .0086528{col 40}{space 1}    8.92{col 49}{space 3}0.000{col 70}{space 3} .1015943
{txt}{space 10}1988  {c |}{col 17}{res}{space 2}  .043067{col 29}{space 2} .0089572{col 40}{space 1}    4.81{col 49}{space 3}0.000{col 70}{space 3} .0533486
{txt}{space 10}1992  {c |}{col 17}{res}{space 2}  .078134{col 29}{space 2}  .008269{col 40}{space 1}    9.45{col 49}{space 3}0.000{col 70}{space 3} .1108324
{txt}{space 10}1996  {c |}{col 17}{res}{space 2} .0788972{col 29}{space 2}  .009099{col 40}{space 1}    8.67{col 49}{space 3}0.000{col 70}{space 3} .0976829
{txt}{space 10}2000  {c |}{col 17}{res}{space 2} .0858039{col 29}{space 2} .0147724{col 40}{space 1}    5.81{col 49}{space 3}0.000{col 70}{space 3} .0552818
{txt}{space 10}2004  {c |}{col 17}{res}{space 2} .0807907{col 29}{space 2} .0103068{col 40}{space 1}    7.84{col 49}{space 3}0.000{col 70}{space 3} .0823131
{txt}{space 10}2008  {c |}{col 17}{res}{space 2}  .177964{col 29}{space 2} .0108054{col 40}{space 1}   16.47{col 49}{space 3}0.000{col 70}{space 3} .1692083
{txt}{space 10}2012  {c |}{col 17}{res}{space 2} .1840086{col 29}{space 2} .0086444{col 40}{space 1}   21.29{col 49}{space 3}0.000{col 70}{space 3} .2487534
{txt}{space 10}2016  {c |}{col 17}{res}{space 2}  .203031{col 29}{space 2} .0100998{col 40}{space 1}   20.10{col 49}{space 3}0.000{col 70}{space 3} .2162932
{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2} .0547024{col 29}{space 2} .0106514{col 40}{space 1}    5.14{col 49}{space 3}0.000{col 70}{space 3}        .
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.         
.         
. * Affective     
. reg ideothermdiff perceivepol2 ideostrength2 pidstrength2 issextreme2 ///
>         sophistication2 edu2 age2 income2 female black south i.year, beta

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}    13,902
{txt}{hline 13}{c +}{hline 34}   F(27, 13874)    = {res}   136.97
{txt}       Model {c |} {res} 1380633.78        27  51134.5845   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 5179694.46    13,874  373.338219   {txt}R-squared       ={res}    0.2105
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.2089
{txt}       Total {c |} {res} 6560328.24    13,901  471.932108   {txt}Root MSE        =   {res} 19.322

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}  ideothermdiff{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 70}        Beta
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}perceivepol2 {c |}{col 17}{res}{space 2} 16.64739{col 29}{space 2} .8193543{col 40}{space 1}   20.32{col 49}{space 3}0.000{col 70}{space 3} .1712613
{txt}{space 2}ideostrength2 {c |}{col 17}{res}{space 2} 24.45303{col 29}{space 2} .6010454{col 40}{space 1}   40.68{col 49}{space 3}0.000{col 70}{space 3} .3216082
{txt}{space 3}pidstrength2 {c |}{col 17}{res}{space 2} 1.207547{col 29}{space 2} .5835559{col 40}{space 1}    2.07{col 49}{space 3}0.039{col 70}{space 3} .0166067
{txt}{space 4}issextreme2 {c |}{col 17}{res}{space 2} 7.246959{col 29}{space 2} .6961273{col 40}{space 1}   10.41{col 49}{space 3}0.000{col 70}{space 3} .0827963
{txt}sophistication2 {c |}{col 17}{res}{space 2}  8.98572{col 29}{space 2} .8911402{col 40}{space 1}   10.08{col 49}{space 3}0.000{col 70}{space 3} .0851026
{txt}{space 11}edu2 {c |}{col 17}{res}{space 2} 3.833163{col 29}{space 2} .6884279{col 40}{space 1}    5.57{col 49}{space 3}0.000{col 70}{space 3} .0482047
{txt}{space 11}age2 {c |}{col 17}{res}{space 2} 6.703921{col 29}{space 2} .8584142{col 40}{space 1}    7.81{col 49}{space 3}0.000{col 70}{space 3} .0616949
{txt}{space 8}income2 {c |}{col 17}{res}{space 2} .1172259{col 29}{space 2} .6597002{col 40}{space 1}    0.18{col 49}{space 3}0.859{col 70}{space 3} .0014669
{txt}{space 9}female {c |}{col 17}{res}{space 2} .1190259{col 29}{space 2} .3326035{col 40}{space 1}    0.36{col 49}{space 3}0.720{col 70}{space 3} .0027392
{txt}{space 10}black {c |}{col 17}{res}{space 2}-3.674824{col 29}{space 2} .5573988{col 40}{space 1}   -6.59{col 49}{space 3}0.000{col 70}{space 3}-.0527748
{txt}{space 10}south {c |}{col 17}{res}{space 2} 1.825716{col 29}{space 2} .3567946{col 40}{space 1}    5.12{col 49}{space 3}0.000{col 70}{space 3} .0394844
{txt}{space 15} {c |}
{space 11}year {c |}
{space 10}1976  {c |}{col 17}{res}{space 2}-5.414235{col 29}{space 2} .8555858{col 40}{space 1}   -6.33{col 49}{space 3}0.000{col 70}{space 3}-.0617075
{txt}{space 10}1980  {c |}{col 17}{res}{space 2}-1.621105{col 29}{space 2} .9618371{col 40}{space 1}   -1.69{col 49}{space 3}0.092{col 70}{space 3}-.0155103
{txt}{space 10}1982  {c |}{col 17}{res}{space 2} -3.59939{col 29}{space 2}  .960075{col 40}{space 1}   -3.75{col 49}{space 3}0.000{col 70}{space 3} -.034775
{txt}{space 10}1984  {c |}{col 17}{res}{space 2}-6.043025{col 29}{space 2} .8475249{col 40}{space 1}   -7.13{col 49}{space 3}0.000{col 70}{space 3}-.0712419
{txt}{space 10}1986  {c |}{col 17}{res}{space 2}-1.513898{col 29}{space 2} .8159845{col 40}{space 1}   -1.86{col 49}{space 3}0.064{col 70}{space 3}-.0192501
{txt}{space 10}1988  {c |}{col 17}{res}{space 2}-3.421861{col 29}{space 2}  .878519{col 40}{space 1}   -3.90{col 49}{space 3}0.000{col 70}{space 3}-.0376783
{txt}{space 10}1990  {c |}{col 17}{res}{space 2}-1.761602{col 29}{space 2} .8599947{col 40}{space 1}   -2.05{col 49}{space 3}0.041{col 70}{space 3}-.0203211
{txt}{space 10}1992  {c |}{col 17}{res}{space 2} -4.74216{col 29}{space 2} .8062217{col 40}{space 1}   -5.88{col 49}{space 3}0.000{col 70}{space 3} -.060864
{txt}{space 10}1994  {c |}{col 17}{res}{space 2} -2.44728{col 29}{space 2} .8676383{col 40}{space 1}   -2.82{col 49}{space 3}0.005{col 70}{space 3}-.0279065
{txt}{space 10}1996  {c |}{col 17}{res}{space 2}-5.324668{col 29}{space 2} .8832269{col 40}{space 1}   -6.03{col 49}{space 3}0.000{col 70}{space 3}-.0594004
{txt}{space 10}1998  {c |}{col 17}{res}{space 2}-2.478142{col 29}{space 2} .9328593{col 40}{space 1}   -2.66{col 49}{space 3}0.008{col 70}{space 3}-.0254291
{txt}{space 10}2000  {c |}{col 17}{res}{space 2} -4.15891{col 29}{space 2} 1.445209{col 40}{space 1}   -2.88{col 49}{space 3}0.004{col 70}{space 3}-.0236239
{txt}{space 10}2004  {c |}{col 17}{res}{space 2}-5.408391{col 29}{space 2} 1.005629{col 40}{space 1}   -5.38{col 49}{space 3}0.000{col 70}{space 3}-.0490775
{txt}{space 10}2008  {c |}{col 17}{res}{space 2}-8.922394{col 29}{space 2} 1.068062{col 40}{space 1}   -8.35{col 49}{space 3}0.000{col 70}{space 3}-.0750663
{txt}{space 10}2012  {c |}{col 17}{res}{space 2}-5.319005{col 29}{space 2} .8537484{col 40}{space 1}   -6.23{col 49}{space 3}0.000{col 70}{space 3}-.0646158
{txt}{space 10}2016  {c |}{col 17}{res}{space 2}-3.657371{col 29}{space 2}   .98831{col 40}{space 1}   -3.70{col 49}{space 3}0.000{col 70}{space 3}-.0350192
{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2}-.2672708{col 29}{space 2} .9221177{col 40}{space 1}   -0.29{col 49}{space 3}0.772{col 70}{space 3}        .
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. reg partydifftherm perceivepol2 ideostrength2 pidstrength2 issextreme2 ///
>         sophistication2 edu2 age2 income2 female black south i.year, beta

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}    13,275
{txt}{hline 13}{c +}{hline 34}   F(26, 13248)    = {res}   260.42
{txt}       Model {c |} {res} 2734251.04        26  105163.502   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 5349828.95    13,248   403.82163   {txt}R-squared       ={res}    0.3382
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.3369
{txt}       Total {c |} {res}    8084080    13,274  609.016121   {txt}Root MSE        =   {res} 20.095

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1} partydifftherm{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 70}        Beta
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}perceivepol2 {c |}{col 17}{res}{space 2} 27.43862{col 29}{space 2} .8676784{col 40}{space 1}   31.62{col 49}{space 3}0.000{col 70}{space 3} .2511218
{txt}{space 2}ideostrength2 {c |}{col 17}{res}{space 2} 9.260353{col 29}{space 2} .6358681{col 40}{space 1}   14.56{col 49}{space 3}0.000{col 70}{space 3} .1076888
{txt}{space 3}pidstrength2 {c |}{col 17}{res}{space 2} 28.30691{col 29}{space 2} .6180536{col 40}{space 1}   45.80{col 49}{space 3}0.000{col 70}{space 3} .3446575
{txt}{space 4}issextreme2 {c |}{col 17}{res}{space 2} 8.515299{col 29}{space 2} .7546061{col 40}{space 1}   11.28{col 49}{space 3}0.000{col 70}{space 3} .0837145
{txt}sophistication2 {c |}{col 17}{res}{space 2} 10.70692{col 29}{space 2} .9484788{col 40}{space 1}   11.29{col 49}{space 3}0.000{col 70}{space 3}  .089108
{txt}{space 11}edu2 {c |}{col 17}{res}{space 2}-5.599552{col 29}{space 2} .7358551{col 40}{space 1}   -7.61{col 49}{space 3}0.000{col 70}{space 3}-.0618295
{txt}{space 11}age2 {c |}{col 17}{res}{space 2} 3.102995{col 29}{space 2} .9054629{col 40}{space 1}    3.43{col 49}{space 3}0.001{col 70}{space 3} .0253957
{txt}{space 8}income2 {c |}{col 17}{res}{space 2}-3.657498{col 29}{space 2} .6991389{col 40}{space 1}   -5.23{col 49}{space 3}0.000{col 70}{space 3}-.0407429
{txt}{space 9}female {c |}{col 17}{res}{space 2} 1.491304{col 29}{space 2} .3545033{col 40}{space 1}    4.21{col 49}{space 3}0.000{col 70}{space 3} .0302106
{txt}{space 10}black {c |}{col 17}{res}{space 2} 5.229372{col 29}{space 2} .5818745{col 40}{space 1}    8.99{col 49}{space 3}0.000{col 70}{space 3} .0675533
{txt}{space 10}south {c |}{col 17}{res}{space 2}-.5496882{col 29}{space 2} .3776332{col 40}{space 1}   -1.46{col 49}{space 3}0.146{col 70}{space 3}-.0105258
{txt}{space 15} {c |}
{space 11}year {c |}
{space 10}1980  {c |}{col 17}{res}{space 2} .0291724{col 29}{space 2} .9908245{col 40}{space 1}    0.03{col 49}{space 3}0.977{col 70}{space 3} .0002577
{txt}{space 10}1982  {c |}{col 17}{res}{space 2} 3.123129{col 29}{space 2} .9917119{col 40}{space 1}    3.15{col 49}{space 3}0.002{col 70}{space 3} .0277055
{txt}{space 10}1984  {c |}{col 17}{res}{space 2} 4.444662{col 29}{space 2} .8853132{col 40}{space 1}    5.02{col 49}{space 3}0.000{col 70}{space 3} .0477313
{txt}{space 10}1986  {c |}{col 17}{res}{space 2} 3.624633{col 29}{space 2} .8511242{col 40}{space 1}    4.26{col 49}{space 3}0.000{col 70}{space 3} .0419116
{txt}{space 10}1988  {c |}{col 17}{res}{space 2} 5.804671{col 29}{space 2}  .913817{col 40}{space 1}    6.35{col 49}{space 3}0.000{col 70}{space 3}  .058397
{txt}{space 10}1990  {c |}{col 17}{res}{space 2} 1.572384{col 29}{space 2} .8944325{col 40}{space 1}    1.76{col 49}{space 3}0.079{col 70}{space 3} .0164639
{txt}{space 10}1992  {c |}{col 17}{res}{space 2} 2.886549{col 29}{space 2} .8478417{col 40}{space 1}    3.40{col 49}{space 3}0.001{col 70}{space 3} .0335665
{txt}{space 10}1994  {c |}{col 17}{res}{space 2} 2.795742{col 29}{space 2} .8998737{col 40}{space 1}    3.11{col 49}{space 3}0.002{col 70}{space 3} .0291172
{txt}{space 10}1996  {c |}{col 17}{res}{space 2} 4.983629{col 29}{space 2} .9193515{col 40}{space 1}    5.42{col 49}{space 3}0.000{col 70}{space 3}  .050402
{txt}{space 10}1998  {c |}{col 17}{res}{space 2} 5.617061{col 29}{space 2} .9602901{col 40}{space 1}    5.85{col 49}{space 3}0.000{col 70}{space 3} .0529136
{txt}{space 10}2000  {c |}{col 17}{res}{space 2} 7.115433{col 29}{space 2} 1.486397{col 40}{space 1}    4.79{col 49}{space 3}0.000{col 70}{space 3} .0369743
{txt}{space 10}2004  {c |}{col 17}{res}{space 2}  6.33774{col 29}{space 2} 1.046484{col 40}{space 1}    6.06{col 49}{space 3}0.000{col 70}{space 3} .0524103
{txt}{space 10}2008  {c |}{col 17}{res}{space 2} 5.080405{col 29}{space 2} 1.109191{col 40}{space 1}    4.58{col 49}{space 3}0.000{col 70}{space 3} .0391196
{txt}{space 10}2012  {c |}{col 17}{res}{space 2} 8.103717{col 29}{space 2} .8947178{col 40}{space 1}    9.06{col 49}{space 3}0.000{col 70}{space 3} .0897369
{txt}{space 10}2016  {c |}{col 17}{res}{space 2} 4.016344{col 29}{space 2} 1.040561{col 40}{space 1}    3.86{col 49}{space 3}0.000{col 70}{space 3} .0346041
{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2}-10.92848{col 29}{space 2} .9979759{col 40}{space 1}  -10.95{col 49}{space 3}0.000{col 70}{space 3}        .
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. reg diffcandtherm perceivepol2 ideostrength2 pidstrength2 issextreme2 ///
>         sophistication2 edu2 age2 income2 female black south i.year, beta

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}     9,883
{txt}{hline 13}{c +}{hline 34}   F(22, 9860)     = {res}   136.75
{txt}       Model {c |} {res}  1694339.6        22  77015.4362   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 5552818.23     9,860  563.166149   {txt}R-squared       ={res}    0.2338
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.2321
{txt}       Total {c |} {res} 7247157.83     9,882  733.369544   {txt}Root MSE        =   {res} 23.731

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}  diffcandtherm{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 70}        Beta
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}perceivepol2 {c |}{col 17}{res}{space 2} 22.29937{col 29}{space 2} 1.169604{col 40}{space 1}   19.07{col 49}{space 3}0.000{col 70}{space 3}  .189815
{txt}{space 2}ideostrength2 {c |}{col 17}{res}{space 2} 8.122373{col 29}{space 2} .8661495{col 40}{space 1}    9.38{col 49}{space 3}0.000{col 70}{space 3} .0865264
{txt}{space 3}pidstrength2 {c |}{col 17}{res}{space 2}  14.3005{col 29}{space 2} .8434391{col 40}{space 1}   16.95{col 49}{space 3}0.000{col 70}{space 3} .1599511
{txt}{space 4}issextreme2 {c |}{col 17}{res}{space 2} 10.06449{col 29}{space 2} .9965086{col 40}{space 1}   10.10{col 49}{space 3}0.000{col 70}{space 3} .0942391
{txt}sophistication2 {c |}{col 17}{res}{space 2} 26.18002{col 29}{space 2}   1.2908{col 40}{space 1}   20.28{col 49}{space 3}0.000{col 70}{space 3} .1980228
{txt}{space 11}edu2 {c |}{col 17}{res}{space 2}-4.661844{col 29}{space 2}   1.0029{col 40}{space 1}   -4.65{col 49}{space 3}0.000{col 70}{space 3}-.0475953
{txt}{space 11}age2 {c |}{col 17}{res}{space 2} 3.244428{col 29}{space 2} 1.237981{col 40}{space 1}    2.62{col 49}{space 3}0.009{col 70}{space 3} .0242355
{txt}{space 8}income2 {c |}{col 17}{res}{space 2}-1.980694{col 29}{space 2} .9636463{col 40}{space 1}   -2.06{col 49}{space 3}0.040{col 70}{space 3}-.0200147
{txt}{space 9}female {c |}{col 17}{res}{space 2}  2.26375{col 29}{space 2} .4849908{col 40}{space 1}    4.67{col 49}{space 3}0.000{col 70}{space 3} .0417835
{txt}{space 10}black {c |}{col 17}{res}{space 2} 1.138609{col 29}{space 2} .7980143{col 40}{space 1}    1.43{col 49}{space 3}0.154{col 70}{space 3} .0134214
{txt}{space 10}south {c |}{col 17}{res}{space 2}-.1793746{col 29}{space 2} .5197761{col 40}{space 1}   -0.35{col 49}{space 3}0.730{col 70}{space 3}-.0031232
{txt}{space 15} {c |}
{space 11}year {c |}
{space 10}1976  {c |}{col 17}{res}{space 2}-10.93421{col 29}{space 2} 1.017016{col 40}{space 1}  -10.75{col 49}{space 3}0.000{col 70}{space 3}-.1212818
{txt}{space 10}1980  {c |}{col 17}{res}{space 2}-6.448492{col 29}{space 2} 1.151513{col 40}{space 1}   -5.60{col 49}{space 3}0.000{col 70}{space 3}-.0598643
{txt}{space 10}1984  {c |}{col 17}{res}{space 2}-1.265027{col 29}{space 2} 1.027317{col 40}{space 1}   -1.23{col 49}{space 3}0.218{col 70}{space 3}-.0141752
{txt}{space 10}1988  {c |}{col 17}{res}{space 2}-5.070788{col 29}{space 2} 1.059294{col 40}{space 1}   -4.79{col 49}{space 3}0.000{col 70}{space 3}-.0534677
{txt}{space 10}1992  {c |}{col 17}{res}{space 2}-7.238624{col 29}{space 2} .9795969{col 40}{space 1}   -7.39{col 49}{space 3}0.000{col 70}{space 3}-.0874018
{txt}{space 10}1996  {c |}{col 17}{res}{space 2}-3.761337{col 29}{space 2} 1.079485{col 40}{space 1}   -3.48{col 49}{space 3}0.000{col 70}{space 3}-.0396403
{txt}{space 10}2000  {c |}{col 17}{res}{space 2}-7.066759{col 29}{space 2} 1.748527{col 40}{space 1}   -4.04{col 49}{space 3}0.000{col 70}{space 3}-.0387555
{txt}{space 10}2004  {c |}{col 17}{res}{space 2} 1.812062{col 29}{space 2}  1.22254{col 40}{space 1}    1.48{col 49}{space 3}0.138{col 70}{space 3} .0157152
{txt}{space 10}2008  {c |}{col 17}{res}{space 2}-6.728677{col 29}{space 2} 1.293532{col 40}{space 1}   -5.20{col 49}{space 3}0.000{col 70}{space 3}-.0544575
{txt}{space 10}2012  {c |}{col 17}{res}{space 2} 4.451178{col 29}{space 2} 1.044553{col 40}{space 1}    4.26{col 49}{space 3}0.000{col 70}{space 3} .0512205
{txt}{space 10}2016  {c |}{col 17}{res}{space 2} 5.921449{col 29}{space 2}  1.21718{col 40}{space 1}    4.86{col 49}{space 3}0.000{col 70}{space 3} .0536965
{txt}{space 15} {c |}
{space 10}_cons {c |}{col 17}{res}{space 2} 8.978722{col 29}{space 2} 1.258072{col 40}{space 1}    7.14{col 49}{space 3}0.000{col 70}{space 3}        .
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.         
.         
. 
{txt}end of do-file

{com}. clear

. use "/Users/adamenders/Dropbox/Perceived vs. Affective Polarization/Data and Code/92-96 Panel/anes_mergedfile_1992to1997.dta"

. do "/var/folders/xb/ddtsf7g93xd57f7hhtnm9lyc0000gp/T//SD59652.000000"
{txt}
{com}. ********************************************************************************
. 
. ****
. ** Data cleaning and recoding
. ****
. 
. * Case ID
. gen id92 = VID92 
{txt}(1,434 missing values generated)

{com}. gen id94 = VID94 
{txt}(644 missing values generated)

{com}. gen id96 = VID96
{txt}(725 missing values generated)

{com}. 
. keep if id92 != . & id96 != .
{txt}(1,842 observations deleted)

{com}. 
. 
. * Weight
. gen weight92 = V923009
{txt}
{com}. gen weight94 = V940005 
{txt}
{com}. gen weight96 = V960004
{txt}
{com}. 
. 
. * Party identification
. gen pid92 = V923634 - 3
{txt}
{com}. replace pid92 = . if pid92 > 3
{txt}(8 real changes made, 8 to missing)

{com}. gen pid94 = V940655 - 3
{txt}
{com}. replace pid94 = . if pid94 > 3
{txt}(3 real changes made, 3 to missing)

{com}. gen pid96 = V960420 - 3
{txt}
{com}. replace pid96 = . if pid96 > 3
{txt}(6 real changes made, 6 to missing)

{com}. 
. gen rep92 = 1 if pid92 > 0 & pid92 < .
{txt}(349 missing values generated)

{com}. replace rep92 = 0 if pid92 < 0
{txt}(278 real changes made)

{com}. gen rep94 = 1 if pid94 > 0 & pid94 < .
{txt}(329 missing values generated)

{com}. replace rep94 = 0 if pid94 < 0
{txt}(279 real changes made)

{com}. gen rep96 = 1 if pid96 > 0 & pid96 < .
{txt}(346 missing values generated)

{com}. replace rep96 = 0 if pid96 < 0
{txt}(298 real changes made)

{com}. 
. 
. * Party ID strength
. gen pidstrength92 = 3 if abs(pid92) == 3
{txt}(432 missing values generated)

{com}. replace pidstrength92 = 2 if abs(pid92) == 2
{txt}(185 real changes made)

{com}. replace pidstrength92 = 1 if abs(pid92) == 1
{txt}(176 real changes made)

{com}. replace pidstrength92 = 0 if abs(pid92) == 0
{txt}(63 real changes made)

{com}. 
. gen pidstrength94 = 3 if abs(pid94) == 3
{txt}(396 missing values generated)

{com}. replace pidstrength94 = 2 if abs(pid94) == 2
{txt}(192 real changes made)

{com}. replace pidstrength94 = 1 if abs(pid94) == 1
{txt}(154 real changes made)

{com}. replace pidstrength94 = 0 if abs(pid94) == 0
{txt}(47 real changes made)

{com}. 
. gen pidstrength96 = 3 if abs(pid96) == 3
{txt}(407 missing values generated)

{com}. replace pidstrength96 = 2 if abs(pid96) == 2
{txt}(208 real changes made)

{com}. replace pidstrength96 = 1 if abs(pid96) == 1
{txt}(151 real changes made)

{com}. replace pidstrength96 = 0 if abs(pid96) == 0
{txt}(42 real changes made)

{com}. 
. 
. * Ideology
. gen ideo92 = V923509 - 4
{txt}
{com}. replace ideo92 = . if abs(ideo92) > 3 
{txt}(122 real changes made, 122 to missing)

{com}. gen ideo94 = V940839 - 4
{txt}
{com}. replace ideo94 = . if abs(ideo94) > 3 
{txt}(95 real changes made, 95 to missing)

{com}. gen ideo96 = V960365 - 4
{txt}
{com}. replace ideo96 = . if abs(ideo96) > 3 
{txt}(101 real changes made, 101 to missing)

{com}. 
. gen conserv92 = 1 if ideo92 > 0 & ideo92 < .
{txt}(391 missing values generated)

{com}. replace conserv92 = 0 if ideo92 < 0
{txt}(132 real changes made)

{com}. gen conserv94 = 1 if ideo94 > 0 & ideo94 < .
{txt}(363 missing values generated)

{com}. replace conserv94 = 0 if ideo94 < 0
{txt}(123 real changes made)

{com}. gen conserv96 = 1 if ideo96 > 0 & ideo96 < .
{txt}(362 missing values generated)

{com}. replace conserv96 = 0 if ideo96 < 0
{txt}(132 real changes made)

{com}. 
. 
. * Ideological strength
. gen ideostrength92 = 3 if abs(ideo92) == 3
{txt}(561 missing values generated)

{com}. replace ideostrength92 = 2 if abs(ideo92) == 2
{txt}(145 real changes made)

{com}. replace ideostrength92 = 1 if abs(ideo92) == 1
{txt}(157 real changes made)

{com}. replace ideostrength92 = 0 if abs(ideo92) == 0
{txt}(137 real changes made)

{com}. 
. gen ideostrength94 = 3 if abs(ideo94) == 3
{txt}(570 missing values generated)

{com}. replace ideostrength94 = 2 if abs(ideo94) == 2
{txt}(166 real changes made)

{com}. replace ideostrength94 = 1 if abs(ideo94) == 1
{txt}(164 real changes made)

{com}. replace ideostrength94 = 0 if abs(ideo94) == 0
{txt}(145 real changes made)

{com}. 
. gen ideostrength96 = 3 if abs(ideo96) == 3
{txt}(573 missing values generated)

{com}. replace ideostrength96 = 2 if abs(ideo96) == 2
{txt}(158 real changes made)

{com}. replace ideostrength96 = 1 if abs(ideo96) == 1
{txt}(185 real changes made)

{com}. replace ideostrength96 = 0 if abs(ideo96) == 0
{txt}(129 real changes made)

{com}. 
. 
. * Sorting
. replace ideostrength92 = ideostrength92 + 1
{txt}(475 real changes made)

{com}. replace pidstrength92 = pidstrength92 + 1
{txt}(589 real changes made)

{com}. gen sorting92 = abs(pid92 - (-1 * ideo92)) * ideostrength92 * pidstrength92
{txt}(124 missing values generated)

{com}. 
. replace ideostrength94 = ideostrength94 + 1
{txt}(502 real changes made)

{com}. replace pidstrength94 = pidstrength94 + 1
{txt}(594 real changes made)

{com}. gen sorting94 = abs(pid94 - (-1 * ideo94)) * ideostrength94 * pidstrength94
{txt}(95 missing values generated)

{com}. 
. replace ideostrength96 = ideostrength96 + 1
{txt}(496 real changes made)

{com}. replace pidstrength96 = pidstrength96 + 1
{txt}(591 real changes made)

{com}. gen sorting96 = abs(pid96 - (-1 * ideo96)) * ideostrength96 * pidstrength96
{txt}(104 missing values generated)

{com}. 
. 
. * Education (ranges from 1-7)
. gen edu92 = V923908
{txt}
{com}. replace edu92 = . if edu92 >= 8
{txt}(20 real changes made, 20 to missing)

{com}. replace edu92 = . if edu92 < 1
{txt}(0 real changes made)

{com}. label define edulab 1 "8 grades or less" 2 "9-12 grades" 3 "High school" ///
>         4 "HS + non-academic training" 5 "Some college" 6 "BA" 7 "Advanced"
{txt}
{com}. label values edu edulab
{txt}
{com}. 
. 
. * Family income (1-24)
. gen income92 = V924104
{txt}
{com}. replace income92 = . if income > 24
{txt}(45 real changes made, 45 to missing)

{com}. 
. 
. * Race 
. gen race92 = V924202
{txt}
{com}. replace race92 = . if race92 == 9
{txt}(1 real change made, 1 to missing)

{com}. 
. gen white92 = 0
{txt}
{com}. replace white92 = 1 if race92 == 1
{txt}(500 real changes made)

{com}. 
. gen black92 = 0
{txt}
{com}. replace black92 = 1 if race92 == 2
{txt}(78 real changes made)

{com}. 
. 
. * Gender (1=female)
. gen female92 = V924201 - 1
{txt}
{com}. replace female92 = . if female92 < 0
{txt}(0 real changes made)

{com}. replace female92 = . if female92 > 1
{txt}(0 real changes made)

{com}. label define genderlab 0 "Male" 1 "Female"
{txt}
{com}. label values female92 genderlab
{txt}
{com}. 
. 
. * Age (number of years) 
. gen age92 = V923903
{txt}
{com}. replace age92 = . if age92 > 91
{txt}(0 real changes made)

{com}. replace age92 = . if age92 < 17
{txt}(0 real changes made)

{com}. 
. 
. * Region
. gen south92 = .
{txt}(597 missing values generated)

{com}. replace south92 = 0 
{txt}(597 real changes made)

{com}. replace south92 = 1 if V923014 == 3
{txt}(218 real changes made)

{com}. label define southern 0 "0 Non-South" 1 "1 South"
{txt}
{com}. label values south southern
{txt}
{com}. 
. 
. * Church attendance
. gen church92 = V923821
{txt}
{com}. replace church92 = . if church92 < 1
{txt}(137 real changes made, 137 to missing)

{com}. recode church92 (5=0) (4=1) (3=2) (2=3) (1=4)
{txt}(church92: 458 changes made)

{com}. 
. 
. * Interest in campaigns 
. gen interest92 = V925102
{txt}
{com}. replace interest92 = . if interest92 > 5
{txt}(2 real changes made, 2 to missing)

{com}. replace interest92 = . if interest92 < 1
{txt}(0 real changes made)

{com}. recode interest92 (1=3) (3=2) (5=1)
{txt}(interest92: 595 changes made)

{com}. label define interestlab 1 "Not much interested" ///
>         2 "Somewhat interested" 3 "Very much interested"
{txt}
{com}. label values interest interestlab
{txt}
{com}. 
. 
. * Interviewer information assessment
. gen info92 = V924205
{txt}
{com}. replace info92 = . if info92 > 9
{txt}(0 real changes made)

{com}. recode info92 (5=0) (4=1) (3=2) (2=3) (1=4)
{txt}(info92: 597 changes made)

{com}. 
. 
. * Party feeling thermometers
. gen reptherm92 = V923318
{txt}
{com}. replace reptherm92 = . if reptherm92 > 100
{txt}(22 real changes made, 22 to missing)

{com}. gen demtherm92 = V923317
{txt}
{com}. replace demtherm92 = . if demtherm92 > 100
{txt}(22 real changes made, 22 to missing)

{com}. gen partydifftherm92 = abs(demtherm92 - reptherm92)
{txt}(24 missing values generated)

{com}. 
. gen reptherm94 = V940302
{txt}
{com}. replace reptherm94 = . if reptherm94 > 100
{txt}(12 real changes made, 12 to missing)

{com}. gen demtherm94 = V940301
{txt}
{com}. replace demtherm94 = . if demtherm94 > 100
{txt}(8 real changes made, 8 to missing)

{com}. gen partydifftherm94 = abs(demtherm94 - reptherm94)
{txt}(12 missing values generated)

{com}. 
. gen reptherm96 = V960293
{txt}
{com}. replace reptherm96 = . if reptherm96 > 100
{txt}(13 real changes made, 13 to missing)

{com}. gen demtherm96 = V960292
{txt}
{com}. replace demtherm96 = . if demtherm96 > 100
{txt}(9 real changes made, 9 to missing)

{com}. gen partydifftherm96 = abs(demtherm96 - reptherm96)
{txt}(13 missing values generated)

{com}. 
. 
. * Candidate feeling thermometers
. gen rcandtherm92 = V923305
{txt}
{com}. replace rcandtherm92 = . if rcandtherm92 > 100
{txt}(7 real changes made, 7 to missing)

{com}. gen dcandtherm92 = V923306
{txt}
{com}. replace dcandtherm92 = . if dcandtherm92 > 100
{txt}(16 real changes made, 16 to missing)

{com}. gen diffcandtherm92 = abs(dcandtherm92 - rcandtherm92)
{txt}(19 missing values generated)

{com}. 
. gen rcandtherm96 = V960273
{txt}
{com}. replace rcandtherm96 = . if rcandtherm96 > 100
{txt}(10 real changes made, 10 to missing)

{com}. gen dcandtherm96 = V960272
{txt}
{com}. replace dcandtherm96 = . if dcandtherm96 > 100
{txt}(2 real changes made, 2 to missing)

{com}. gen diffcandtherm96 = abs(dcandtherm96 - rcandtherm96)
{txt}(11 missing values generated)

{com}. 
. 
. * Ideological group feeling thermometers
. gen contherm92 = V925319
{txt}
{com}. replace contherm92 = . if contherm92 > 100
{txt}(33 real changes made, 33 to missing)

{com}. gen libtherm92 = V925326
{txt}
{com}. replace libtherm92 = . if libtherm92 > 100
{txt}(28 real changes made, 28 to missing)

{com}. gen diffideotherm92 = abs(libtherm92 - contherm92)
{txt}(39 missing values generated)

{com}. 
. gen contherm94 = V940306
{txt}
{com}. replace contherm94 = . if contherm94 > 100
{txt}(28 real changes made, 28 to missing)

{com}. gen libtherm94 = V940311
{txt}
{com}. replace libtherm94 = . if libtherm94 > 100
{txt}(19 real changes made, 19 to missing)

{com}. gen diffideotherm94 = abs(libtherm94 - contherm94)
{txt}(32 missing values generated)

{com}. 
. gen contherm96 = V961031
{txt}
{com}. replace contherm96 = . if contherm96 > 100
{txt}(71 real changes made, 71 to missing)

{com}. gen libtherm96 = V961032
{txt}
{com}. replace libtherm96 = . if libtherm96 > 100
{txt}(71 real changes made, 71 to missing)

{com}. gen diffideotherm96 = abs(libtherm96 - contherm96)
{txt}(74 missing values generated)

{com}. 
. 
. * Affective polarization
. factor diffideotherm92 diffcandtherm92 partydifftherm92, ipf
{txt}(obs=538)

Factor analysis/correlation{col 50}Number of obs    = {res}       538
{col 5}{txt}Method: iterated principal factors{col 50}Retained factors =   {res}       2
{col 5}{txt}Rotation: (unrotated){col 50}Number of params =   {res}       3

{txt}{col 5}{hline 13}{c TT}{hline 60}
{col 5}     Factor  {c |} {ralign 12:Eigenvalue}   Difference        Proportion   Cumulative
{col 5}{hline 13}{c +}{hline 60}
{col 5}{ralign 11:Factor1}  {c |}{res}      1.40399      1.38431            0.9863       0.9863
{txt}{col 5}{ralign 11:Factor2}  {c |}{res}      0.01967      0.01981            0.0138       1.0001
{txt}{col 5}{ralign 11:Factor3}  {c |}{res}     -0.00013            .           -0.0001       1.0000
{txt}{col 5}{hline 13}{c BT}{hline 60}
{col 5}LR test: independent vs. saturated:  chi2({res}3{txt})  ={res}  328.63{txt} Prob>chi2 ={res} 0.0000

{txt}Factor loadings (pattern matrix) and unique variances

{space 4}{hline 13}{c  TT}{hline 10}{hline 10}{c  TT}{hline 14}
{space 4}{space 0}{ralign 12:Variable}{space 1}{c |}{space 1}{ralign 8:Factor1}{space 1}{space 1}{ralign 8:Factor2}{space 1}{c |}{space 1}{ralign 12:Uniqueness}{space 1}
{space 4}{hline 13}{c   +}{hline 10}{hline 10}{c   +}{hline 14}
{space 4}{space 0}{ralign 12:diffideot~92}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.4215}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.1235}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.8070}}}{space 1}
{space 4}{space 0}{ralign 12:diffcandt~92}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.7945}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0011}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.3688}}}{space 1}
{space 4}{space 0}{ralign 12:partydiff~92}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.7715}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0664}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.4005}}}{space 1}
{space 4}{hline 13}{c  BT}{hline 10}{hline 10}{c  BT}{hline 14}

{com}. alpha diffideotherm92 diffcandtherm92 partydifftherm92, gen(affectpol92)

{txt}Test scale = mean(unstandardized items)

Average interitem covariance:{col 34}{res} 259.8027
{txt}Number of items in the scale:{col 34}{res}        3
{txt}Scale reliability coefficient:{col 34}{res}   0.6884
{txt}
{com}. 
. factor diffideotherm96 diffcandtherm96 partydifftherm96, ipf
{txt}(obs=511)

Factor analysis/correlation{col 50}Number of obs    = {res}       511
{col 5}{txt}Method: iterated principal factors{col 50}Retained factors =   {res}       2
{col 5}{txt}Rotation: (unrotated){col 50}Number of params =   {res}       3

{txt}{col 5}{hline 13}{c TT}{hline 60}
{col 5}     Factor  {c |} {ralign 12:Eigenvalue}   Difference        Proportion   Cumulative
{col 5}{hline 13}{c +}{hline 60}
{col 5}{ralign 11:Factor1}  {c |}{res}      1.68544      1.65523            0.9825       0.9825
{txt}{col 5}{ralign 11:Factor2}  {c |}{res}      0.03021      0.03033            0.0176       1.0001
{txt}{col 5}{ralign 11:Factor3}  {c |}{res}     -0.00012            .           -0.0001       1.0000
{txt}{col 5}{hline 13}{c BT}{hline 60}
{col 5}LR test: independent vs. saturated:  chi2({res}3{txt})  ={res}  475.16{txt} Prob>chi2 ={res} 0.0000

{txt}Factor loadings (pattern matrix) and unique variances

{space 4}{hline 13}{c  TT}{hline 10}{hline 10}{c  TT}{hline 14}
{space 4}{space 0}{ralign 12:Variable}{space 1}{c |}{space 1}{ralign 8:Factor1}{space 1}{space 1}{ralign 8:Factor2}{space 1}{c |}{space 1}{ralign 12:Uniqueness}{space 1}
{space 4}{hline 13}{c   +}{hline 10}{hline 10}{c   +}{hline 14}
{space 4}{space 0}{ralign 12:diffideot~96}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.5294}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.1420}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.6995}}}{space 1}
{space 4}{space 0}{ralign 12:diffcandt~96}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.8123}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.1000}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.3302}}}{space 1}
{space 4}{space 0}{ralign 12:partydiff~96}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.8633}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0070}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.2546}}}{space 1}
{space 4}{hline 13}{c  BT}{hline 10}{hline 10}{c  BT}{hline 14}

{com}. alpha diffideotherm96 diffcandtherm96 partydifftherm96, gen(affectpol96)

{txt}Test scale = mean(unstandardized items)

Average interitem covariance:{col 34}{res} 339.1357
{txt}Number of items in the scale:{col 34}{res}        3
{txt}Scale reliability coefficient:{col 34}{res}   0.7683
{txt}
{com}. 
. 
. * Party ideology
. gen repideo92 = V923517
{txt}
{com}. replace repideo92 = . if repideo92 < 1
{txt}(28 real changes made, 28 to missing)

{com}. replace repideo92 = . if repideo92 > 7
{txt}(71 real changes made, 71 to missing)

{com}. gen demideo92 = V923518
{txt}
{com}. replace demideo92 = . if demideo92 < 1
{txt}(28 real changes made, 28 to missing)

{com}. replace demideo92 = . if demideo92 > 7
{txt}(65 real changes made, 65 to missing)

{com}. gen pdiffideo92 = abs(repideo92 - demideo92)
{txt}(101 missing values generated)

{com}. 
. gen repideo96 = V960380
{txt}
{com}. replace repideo96 = . if repideo96 < 1
{txt}(15 real changes made, 15 to missing)

{com}. replace repideo96 = . if repideo96 > 7
{txt}(24 real changes made, 24 to missing)

{com}. gen demideo96 = V960379
{txt}
{com}. replace demideo96 = . if demideo96 < 1
{txt}(15 real changes made, 15 to missing)

{com}. replace demideo96 = . if demideo96 > 7
{txt}(22 real changes made, 22 to missing)

{com}. gen pdiffideo96 = abs(repideo96 - demideo96)
{txt}(44 missing values generated)

{com}. 
. 
. * Government spending and services
. gen selfservice92 = V923701
{txt}
{com}. replace selfservice92 = . if selfservice92 < 1
{txt}(76 real changes made, 76 to missing)

{com}. replace selfservice92 = . if selfservice92 >= 8
{txt}(3 real changes made, 3 to missing)

{com}. recode selfservice92 (1=3) (2=2) (3=1) (4=0) (5=-1) (6=-2) (7=-3)
{txt}(selfservice92: 456 changes made)

{com}. label values selfservice92 servicelab
{txt}
{com}. 
. gen repservice92 = V923702
{txt}
{com}. replace repservice92 = . if repservice92 < 1
{txt}(79 real changes made, 79 to missing)

{com}. replace repservice92 = . if repservice92 >= 8
{txt}(30 real changes made, 30 to missing)

{com}. recode repservice92 (1=3) (2=2) (3=1) (4=0) (5=-1) (6=-2) (7=-3)
{txt}(repservice92: 375 changes made)

{com}. 
. gen demservice92 = V923703
{txt}
{com}. replace demservice92 = . if demservice92 < 1
{txt}(79 real changes made, 79 to missing)

{com}. replace demservice92 = . if demservice92 >= 8
{txt}(40 real changes made, 40 to missing)

{com}. recode demservice92 (1=3) (2=2) (3=1) (4=0) (5=-1) (6=-2) (7=-3)
{txt}(demservice92: 456 changes made)

{com}. 
. gen pdiffservice92 = abs(repservice92 - demservice92)
{txt}(125 missing values generated)

{com}. 
. 
. gen selfservice96 = V960450
{txt}
{com}. replace selfservice96 = . if selfservice96 < 1
{txt}(67 real changes made, 67 to missing)

{com}. replace selfservice96 = . if selfservice96 >= 8
{txt}(3 real changes made, 3 to missing)

{com}. recode selfservice96 (1=3) (2=2) (3=1) (4=0) (5=-1) (6=-2) (7=-3)
{txt}(selfservice96: 454 changes made)

{com}. 
. gen repservice96 = V960455
{txt}
{com}. replace repservice96 = . if repservice96 < 1
{txt}(0 real changes made)

{com}. replace repservice96 = . if repservice96 >= 8
{txt}(49 real changes made, 49 to missing)

{com}. recode repservice96 (1=3) (2=2) (3=1) (4=0) (5=-1) (6=-2) (7=-3)
{txt}(repservice96: 404 changes made)

{com}. 
. gen demservice96 = V960453
{txt}
{com}. replace demservice96 = . if demservice96 < 1
{txt}(0 real changes made)

{com}. replace demservice96 = . if demservice96 >= 8
{txt}(24 real changes made, 24 to missing)

{com}. recode demservice96 (1=3) (2=2) (3=1) (4=0) (5=-1) (6=-2) (7=-3)
{txt}(demservice96: 558 changes made)

{com}. 
. gen pdiffservice96 = abs(repservice96 - demservice96)
{txt}(54 missing values generated)

{com}. 
. 
. * Defense spending
. gen selfdefense92 = V923707
{txt}
{com}. replace selfdefense92 = . if selfdefense92 < 1
{txt}(56 real changes made, 56 to missing)

{com}. replace selfdefense92 = . if selfdefense92 >= 8
{txt}(4 real changes made, 4 to missing)

{com}. recode selfdefense92 (1=-3) (2=-2) (3=-1) (4=0) (5=1) (6=2) (7=3)
{txt}(selfdefense92: 537 changes made)

{com}. label define defenselab -3 "Greatly decrease defense spending" ///
>         3 "Greatly increase defense spending"
{txt}
{com}. label values selfdefense92 defenselab
{txt}
{com}. 
. gen repdefense92 = V923708
{txt}
{com}. replace repdefense92 = . if repdefense92 < 1
{txt}(60 real changes made, 60 to missing)

{com}. replace repdefense92 = . if repdefense92 >= 8
{txt}(19 real changes made, 19 to missing)

{com}. recode repdefense92 (1=-3) (2=-2) (3=-1) (4=0) (5=1) (6=2) (7=3)
{txt}(repdefense92: 518 changes made)

{com}. 
. gen demdefense92 = V923709
{txt}
{com}. replace demdefense92 = . if demdefense92 < 1
{txt}(60 real changes made, 60 to missing)

{com}. replace demdefense92 = . if demdefense92 >= 8
{txt}(69 real changes made, 69 to missing)

{com}. recode demdefense92 (1=-3) (2=-2) (3=-1) (4=0) (5=1) (6=2) (7=3)
{txt}(demdefense92: 468 changes made)

{com}. 
. gen pdiffdefense92 = abs(repdefense92 - demdefense92)
{txt}(130 missing values generated)

{com}. 
. 
. gen selfdefense96 = V960463
{txt}
{com}. replace selfdefense96 = . if selfdefense96 < 1
{txt}(62 real changes made, 62 to missing)

{com}. replace selfdefense96 = . if selfdefense96 >= 8
{txt}(2 real changes made, 2 to missing)

{com}. recode selfdefense96 (1=-3) (2=-2) (3=-1) (4=0) (5=1) (6=2) (7=3)
{txt}(selfdefense96: 533 changes made)

{com}. 
. gen repdefense96 = V960469
{txt}
{com}. replace repdefense96 = . if repdefense96 < 1
{txt}(0 real changes made)

{com}. replace repdefense96 = . if repdefense96 >= 8
{txt}(69 real changes made, 69 to missing)

{com}. recode repdefense96 (1=-3) (2=-2) (3=-1) (4=0) (5=1) (6=2) (7=3)
{txt}(repdefense96: 528 changes made)

{com}. 
. gen demdefense96 = V960466
{txt}
{com}. replace demdefense96 = . if demdefense96 < 1
{txt}(0 real changes made)

{com}. replace demdefense96 = . if demdefense96 >= 8
{txt}(36 real changes made, 36 to missing)

{com}. recode demdefense96 (1=-3) (2=-2) (3=-1) (4=0) (5=1) (6=2) (7=3)
{txt}(demdefense96: 561 changes made)

{com}. 
. gen pdiffdefense96 = abs(repdefense96 - demdefense96)
{txt}(73 missing values generated)

{com}. 
. 
. * Health insurance
. gen selfinsure92 = V923716
{txt}
{com}. replace selfinsure92 = . if selfinsure92 < 1
{txt}(63 real changes made, 63 to missing)

{com}. replace selfinsure92 = . if selfinsure92 > 7
{txt}(12 real changes made, 12 to missing)

{com}. recode selfinsure92 (1=-3) (2=-2) (3=-1) (4=0) (5=1) (6=2) (7=3)
{txt}(selfinsure92: 522 changes made)

{com}. label define insurelab -3 "Government insurance plan" 3 "Private insurance plan"
{txt}
{com}. label values selfinsure92 insurelab
{txt}
{com}. 
. 
. gen selfinsure96 = V960479
{txt}
{com}. replace selfinsure96 = . if selfinsure96 < 1
{txt}(52 real changes made, 52 to missing)

{com}. replace selfinsure96 = . if selfinsure96 > 7
{txt}(7 real changes made, 7 to missing)

{com}. recode selfinsure96 (1=-3) (2=-2) (3=-1) (4=0) (5=1) (6=2) (7=3)
{txt}(selfinsure96: 538 changes made)

{com}. 
. gen repinsure96 = V960481
{txt}
{com}. replace repinsure96 = . if repinsure96 < 1
{txt}(0 real changes made)

{com}. replace repinsure96 = . if repinsure96 > 7
{txt}(80 real changes made, 80 to missing)

{com}. recode repinsure96 (1=-3) (2=-2) (3=-1) (4=0) (5=1) (6=2) (7=3)
{txt}(repinsure96: 517 changes made)

{com}. 
. gen deminsure96 = V960480
{txt}
{com}. replace deminsure96 = . if deminsure96 < 1
{txt}(0 real changes made)

{com}. replace deminsure96 = . if deminsure96 > 7
{txt}(40 real changes made, 40 to missing)

{com}. recode deminsure96 (1=-3) (2=-2) (3=-1) (4=0) (5=1) (6=2) (7=3)
{txt}(deminsure96: 557 changes made)

{com}. 
. gen pdiffinsure96 = abs(repinsure96 - deminsure96)
{txt}(89 missing values generated)

{com}. 
. 
. * Guarenteed jobs
. gen selfjobs92 = V923718
{txt}
{com}. replace selfjobs92 = . if selfjobs92 < 1
{txt}(50 real changes made, 50 to missing)

{com}. replace selfjobs92 = . if selfjobs92 >= 8
{txt}(5 real changes made, 5 to missing)

{com}. recode selfjobs92 (1=-3) (2=-2) (3=-1) (4=0) (5=1) (6=2) (7=3)
{txt}(selfjobs92: 542 changes made)

{com}. label define jobslab -3 "Government see to job and good standard of living" ///
>         3 "Government let each person get ahead on his own"
{txt}
{com}. label values selfjobs92 jobslab
{txt}
{com}. 
. gen repjobs92 = V923719
{txt}
{com}. replace repjobs92 = . if repjobs92 < 1
{txt}(2 real changes made, 2 to missing)

{com}. replace repjobs92 = . if repjobs92 >= 8
{txt}(55 real changes made, 55 to missing)

{com}. recode repjobs92 (1=-3) (2=-2) (3=-1) (4=0) (5=1) (6=2) (7=3)
{txt}(repjobs92: 540 changes made)

{com}. 
. gen demjobs92 = V923720
{txt}
{com}. replace demjobs92 = . if demjobs92 < 1
{txt}(2 real changes made, 2 to missing)

{com}. replace demjobs92 = . if demjobs92 >= 8
{txt}(83 real changes made, 83 to missing)

{com}. recode demjobs92 (1=-3) (2=-2) (3=-1) (4=0) (5=1) (6=2) (7=3)
{txt}(demjobs92: 512 changes made)

{com}. 
. gen pdiffjobs92 = abs(repjobs92 - demjobs92)
{txt}(93 missing values generated)

{com}. 
. 
. gen selfjobs96 = V960483
{txt}
{com}. replace selfjobs96 = . if selfjobs96 < 1
{txt}(44 real changes made, 44 to missing)

{com}. replace selfjobs96 = . if selfjobs96 >= 8
{txt}(3 real changes made, 3 to missing)

{com}. recode selfjobs96 (1=-3) (2=-2) (3=-1) (4=0) (5=1) (6=2) (7=3)
{txt}(selfjobs96: 550 changes made)

{com}. 
. gen repjobs96 = V960485
{txt}
{com}. replace repjobs96 = . if repjobs96 < 1
{txt}(0 real changes made)

{com}. replace repjobs96 = . if repjobs96 >= 8
{txt}(60 real changes made, 60 to missing)

{com}. recode repjobs96 (1=-3) (2=-2) (3=-1) (4=0) (5=1) (6=2) (7=3)
{txt}(repjobs96: 537 changes made)

{com}. 
. gen demjobs96 = V960484
{txt}
{com}. replace demjobs96 = . if demjobs96 < 1
{txt}(0 real changes made)

{com}. replace demjobs96 = . if demjobs96 >= 8
{txt}(44 real changes made, 44 to missing)

{com}. recode demjobs96 (1=-3) (2=-2) (3=-1) (4=0) (5=1) (6=2) (7=3)
{txt}(demjobs96: 553 changes made)

{com}. 
. gen pdiffjobs96 = abs(repjobs96 - demjobs96)
{txt}(65 missing values generated)

{com}. 
. 
. * Aid to blacks
. gen selfaid92 = V923724
{txt}
{com}. replace selfaid92 = . if selfaid92 == 0
{txt}(44 real changes made, 44 to missing)

{com}. replace selfaid92 = . if selfaid92 >= 8
{txt}(8 real changes made, 8 to missing)

{com}. recode selfaid92 (1=-3) (2=-2) (3=-1) (4=0) (5=1) (6=2) (7=3)
{txt}(selfaid92: 545 changes made)

{com}. label define aidlab -3 "Government should help minority groups" ///
>         3 "Minority groups should help themselves"
{txt}
{com}. label values selfaid92 aidlab
{txt}
{com}. 
. 
. gen selfaid96 = V960487
{txt}
{com}. replace selfaid96 = . if selfaid96 == 0
{txt}(47 real changes made, 47 to missing)

{com}. replace selfaid96 = . if selfaid96 >= 8
{txt}(2 real changes made, 2 to missing)

{com}. recode selfaid96 (1=-3) (2=-2) (3=-1) (4=0) (5=1) (6=2) (7=3)
{txt}(selfaid96: 548 changes made)

{com}. 
. gen repaid96 = V960492
{txt}
{com}. replace repaid96 = . if repaid96 == 0
{txt}(0 real changes made)

{com}. replace repaid96 = . if repaid96 >= 8
{txt}(82 real changes made, 82 to missing)

{com}. recode repaid96 (1=-3) (2=-2) (3=-1) (4=0) (5=1) (6=2) (7=3)
{txt}(repaid96: 515 changes made)

{com}. 
. gen demaid96 = V960490
{txt}
{com}. replace demaid96 = . if demaid96 == 0
{txt}(0 real changes made)

{com}. replace demaid96 = . if demaid96 >= 8
{txt}(57 real changes made, 57 to missing)

{com}. recode demaid96 (1=-3) (2=-2) (3=-1) (4=0) (5=1) (6=2) (7=3)
{txt}(demaid96: 540 changes made)

{com}. 
. gen pdiffaid96 = abs(repaid96 - demaid96)
{txt}(87 missing values generated)

{com}. 
. 
. * Perceived polarization
. factor pdiffideo92 pdiffservice92 pdiffdefense92 ///
>         pdiffjobs92, ipf
{txt}(obs=359)

Factor analysis/correlation{col 50}Number of obs    = {res}       359
{col 5}{txt}Method: iterated principal factors{col 50}Retained factors =   {res}       3
{col 5}{txt}Rotation: (unrotated){col 50}Number of params =   {res}       6

{txt}{col 5}{hline 13}{c TT}{hline 60}
{col 5}     Factor  {c |} {ralign 12:Eigenvalue}   Difference        Proportion   Cumulative
{col 5}{hline 13}{c +}{hline 60}
{col 5}{ralign 11:Factor1}  {c |}{res}      1.49491      1.47709            0.9804       0.9804
{txt}{col 5}{ralign 11:Factor2}  {c |}{res}      0.01782      0.00568            0.0117       0.9921
{txt}{col 5}{ralign 11:Factor3}  {c |}{res}      0.01215      0.01224            0.0080       1.0001
{txt}{col 5}{ralign 11:Factor4}  {c |}{res}     -0.00010            .           -0.0001       1.0000
{txt}{col 5}{hline 13}{c BT}{hline 60}
{col 5}LR test: independent vs. saturated:  chi2({res}6{txt})  ={res}  235.78{txt} Prob>chi2 ={res} 0.0000

{txt}Factor loadings (pattern matrix) and unique variances

{space 4}{hline 13}{c  TT}{hline 10}{hline 10}{hline 10}{c  TT}{hline 14}
{space 4}{space 0}{ralign 12:Variable}{space 1}{c |}{space 1}{ralign 8:Factor1}{space 1}{space 1}{ralign 8:Factor2}{space 1}{space 1}{ralign 8:Factor3}{space 1}{c |}{space 1}{ralign 12:Uniqueness}{space 1}
{space 4}{hline 13}{c   +}{hline 10}{hline 10}{hline 10}{c   +}{hline 14}
{space 4}{space 0}{ralign 12:pdiffideo92}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.4411}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.1162}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0141}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.7917}}}{space 1}
{space 4}{space 0}{ralign 12:pdiffserv~92}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.7587}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0055}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0216}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.4238}}}{space 1}
{space 4}{space 0}{ralign 12:pdiffdefe~92}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.4586}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0409}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0961}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.7788}}}{space 1}
{space 4}{space 0}{ralign 12:pdiffjobs92}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.7172}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0511}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0473}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.4808}}}{space 1}
{space 4}{hline 13}{c  BT}{hline 10}{hline 10}{hline 10}{c  BT}{hline 14}

{com}. alpha pdiffideo92 pdiffservice92 pdiffdefense92 ///
>         pdiffjobs92, gen(ppol92)

{txt}Test scale = mean(unstandardized items)

Average interitem covariance:{col 34}{res} .7439592
{txt}Number of items in the scale:{col 34}{res}        4
{txt}Scale reliability coefficient:{col 34}{res}   0.6803
{txt}
{com}. 
. factor pdiffideo96 pdiffjobs96 pdiffdefense96 ///
>         pdiffservice96, ipf     
{txt}(obs=462)

Factor analysis/correlation{col 50}Number of obs    = {res}       462
{col 5}{txt}Method: iterated principal factors{col 50}Retained factors =   {res}       3
{col 5}{txt}Rotation: (unrotated){col 50}Number of params =   {res}       6

{txt}{col 5}{hline 13}{c TT}{hline 60}
{col 5}     Factor  {c |} {ralign 12:Eigenvalue}   Difference        Proportion   Cumulative
{col 5}{hline 13}{c +}{hline 60}
{col 5}{ralign 11:Factor1}  {c |}{res}      1.93615      1.92246            0.9907       0.9907
{txt}{col 5}{ralign 11:Factor2}  {c |}{res}      0.01369      0.00918            0.0070       0.9977
{txt}{col 5}{ralign 11:Factor3}  {c |}{res}      0.00452      0.00461            0.0023       1.0000
{txt}{col 5}{ralign 11:Factor4}  {c |}{res}     -0.00009            .           -0.0000       1.0000
{txt}{col 5}{hline 13}{c BT}{hline 60}
{col 5}LR test: independent vs. saturated:  chi2({res}6{txt})  ={res}  523.20{txt} Prob>chi2 ={res} 0.0000

{txt}Factor loadings (pattern matrix) and unique variances

{space 4}{hline 13}{c  TT}{hline 10}{hline 10}{hline 10}{c  TT}{hline 14}
{space 4}{space 0}{ralign 12:Variable}{space 1}{c |}{space 1}{ralign 8:Factor1}{space 1}{space 1}{ralign 8:Factor2}{space 1}{space 1}{ralign 8:Factor3}{space 1}{c |}{space 1}{ralign 12:Uniqueness}{space 1}
{space 4}{hline 13}{c   +}{hline 10}{hline 10}{hline 10}{c   +}{hline 14}
{space 4}{space 0}{ralign 12:pdiffideo96}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.4708}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0870}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0378}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.7694}}}{space 1}
{space 4}{space 0}{ralign 12:pdiffjobs96}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.8095}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0146}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0234}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.3439}}}{space 1}
{space 4}{space 0}{ralign 12:pdiffdefe~96}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.6529}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0732}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0397}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.5668}}}{space 1}
{space 4}{space 0}{ralign 12:pdiffserv~96}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.7956}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0235}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0311}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.3656}}}{space 1}
{space 4}{hline 13}{c  BT}{hline 10}{hline 10}{hline 10}{c  BT}{hline 14}

{com}. alpha pdiffideo96 pdiffjobs96 pdiffdefense96 ///
>         pdiffservice96, gen(ppol96) 

{txt}Test scale = mean(unstandardized items)

Average interitem covariance:{col 34}{res} .9597619
{txt}Number of items in the scale:{col 34}{res}        4
{txt}Scale reliability coefficient:{col 34}{res}   0.7627
{txt}
{com}. 
. * Issue extremity
. gen issex1 = abs(selfdefense92)
{txt}(60 missing values generated)

{com}. gen issex2 = abs(selfservice92) 
{txt}(79 missing values generated)

{com}. gen issex3 = abs(selfaid92)     
{txt}(52 missing values generated)

{com}. gen issex4 = abs(selfinsure92)  
{txt}(75 missing values generated)

{com}. gen issex5 = abs(selfjobs92)    
{txt}(55 missing values generated)

{com}.         
. alpha issex1-issex5, gen(issextreme92)

{txt}Test scale = mean(unstandardized items)

Average interitem covariance:{col 34}{res} .2120501
{txt}Number of items in the scale:{col 34}{res}        5
{txt}Scale reliability coefficient:{col 34}{res}   0.5345
{txt}
{com}. 
. ********************************************************************************
.         
. ****
. ** Supplemental Appendix Analyses
. ****    
. 
. foreach v of var ppol96 ppol92 affectpol96 affectpol92 pidstrength92 ///
>         ideostrength92 interest92 info92 edu92 age92 income92{c -(}
{txt}  2{com}.         su `v', meanonly 
{txt}  3{com}.         replace `v' = (`v' - r(min))/(r(max) - r(min)) 
{txt}  4{com}. {c )-}       
{txt}(565 real changes made)
(545 real changes made)
(578 real changes made)
(570 real changes made)
(589 real changes made)
(475 real changes made)
(595 real changes made)
(576 real changes made)
(577 real changes made)
(597 real changes made)
(552 real changes made)

{com}. 
. 
. * Model robustness
. sem (ppol96 <- ppol92 affectpol92) ///
>         (affectpol96 <- affectpol92 ppol92) if rep96 != ., standardized
{res}{txt}(28 observations with missing values excluded)

Endogenous variables

{p 0 11 2}Observed:{space 2}{res}ppol96 affectpol96{p_end}
{txt}
Exogenous variables

{p 0 11 2}Observed:{space 2}{res}ppol92 affectpol92{p_end}
{txt}
Fitting target model:

Iteration 0:{space 3}log likelihood = {res: 581.07295}  
Iteration 1:{space 3}log likelihood = {res: 581.07295}  

{col 1}Structural equation model{col 49}Number of obs{col 67}= {res}       521
{txt}{col 1}Estimation method{col 20}= {res}ml
{txt}{col 1}Log likelihood{col 20}= {res} 581.07295

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}      OIM
{col 1}   Standardized{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}Structural     {col 17}{txt}{c |}
{space 2}{col 3}ppol96       {col 17}{c |}
{space 9}ppol92 {c |}{col 17}{res}{space 2} .3022651{col 29}{space 2} .0422096{col 40}{space 1}    7.16{col 49}{space 3}0.000{col 57}{space 4} .2195358{col 70}{space 3} .3849945
{txt}{space 4}affectpol92 {c |}{col 17}{res}{space 2} .1546085{col 29}{space 2}  .044013{col 40}{space 1}    3.51{col 49}{space 3}0.000{col 57}{space 4} .0683446{col 70}{space 3} .2408724
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 1.340552{col 29}{space 2} .1234459{col 40}{space 1}   10.86{col 49}{space 3}0.000{col 57}{space 4} 1.098603{col 70}{space 3} 1.582502
{space 2}{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}affectpol96  {col 17}{c |}
{space 9}ppol92 {c |}{col 17}{res}{space 2} .1127186{col 29}{space 2} .0409964{col 40}{space 1}    2.75{col 49}{space 3}0.006{col 57}{space 4} .0323672{col 70}{space 3}   .19307
{txt}{space 4}affectpol92 {c |}{col 17}{res}{space 2} .4682053{col 29}{space 2} .0359287{col 40}{space 1}   13.03{col 49}{space 3}0.000{col 57}{space 4} .3977863{col 70}{space 3} .5386242
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .6363517{col 29}{space 2} .1018617{col 40}{space 1}    6.25{col 49}{space 3}0.000{col 57}{space 4} .4367064{col 70}{space 3} .8359969
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}var(e.ppol96){c |}{col 17}{res}{space 2} .8443673{col 29}{space 2} .0280286{col 57}{space 4} .7911811{col 70}{space 3} .9011288
{txt}var(e.affect~96){c |}{col 17}{res}{space 2} .7224943{col 29}{space 2} .0309489{col 57}{space 4} .6643121{col 70}{space 3} .7857722
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
LR test of model vs. saturated: chi2({res:1})   = {res:   126.17}, Prob > chi2 = {res}0.0000
{txt}
{com}. 
. sem (ppol96 <- ppol92 affectpol92 pidstrength92 ideostrength92 ///
>         interest92 info92 edu92 age92 income92 female92 ///
>         black92 south92) ///
>         (affectpol96 <- affectpol92 ppol92 pidstrength92 ideostrength92   ///
>         interest92 info92 edu92 age92 income92 female92  ///
>         black92 south92) if rep96 != ., standardized    
{res}{txt}(152 observations with missing values excluded)

Endogenous variables

{p 0 11 2}Observed:{space 2}{res}ppol96 affectpol96{p_end}
{txt}
Exogenous variables

{p 0 11 2}Observed:{space 2}{res}ppol92 affectpol92 pidstrength92 ideostrength92 interest92 info92 edu92 age92 income92 female92 black92 south92{p_end}
{txt}
Fitting target model:

Iteration 0:{space 3}log likelihood = {res:-214.02192}  
Iteration 1:{space 3}log likelihood = {res:-214.02192}  

{col 1}Structural equation model{col 49}Number of obs{col 67}= {res}       397
{txt}{col 1}Estimation method{col 20}= {res}ml
{txt}{col 1}Log likelihood{col 20}= {res}-214.02192

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}      OIM
{col 1}   Standardized{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}Structural     {col 17}{txt}{c |}
{space 2}{col 3}ppol96       {col 17}{c |}
{space 9}ppol92 {c |}{col 17}{res}{space 2} .3339127{col 29}{space 2} .0479436{col 40}{space 1}    6.96{col 49}{space 3}0.000{col 57}{space 4} .2399449{col 70}{space 3} .4278805
{txt}{space 4}affectpol92 {c |}{col 17}{res}{space 2}  .165307{col 29}{space 2} .0529937{col 40}{space 1}    3.12{col 49}{space 3}0.002{col 57}{space 4} .0614414{col 70}{space 3} .2691727
{txt}{space 2}pidstrength92 {c |}{col 17}{res}{space 2} .0417954{col 29}{space 2} .0480529{col 40}{space 1}    0.87{col 49}{space 3}0.384{col 57}{space 4}-.0523865{col 70}{space 3} .1359772
{txt}{space 2}ideostreng~92 {c |}{col 17}{res}{space 2}-.0218464{col 29}{space 2} .0477217{col 40}{space 1}   -0.46{col 49}{space 3}0.647{col 57}{space 4}-.1153793{col 70}{space 3} .0716864
{txt}{space 5}interest92 {c |}{col 17}{res}{space 2}-.0571688{col 29}{space 2}  .047179{col 40}{space 1}   -1.21{col 49}{space 3}0.226{col 57}{space 4}-.1496381{col 70}{space 3} .0353004
{txt}{space 9}info92 {c |}{col 17}{res}{space 2}  .135324{col 29}{space 2} .0522139{col 40}{space 1}    2.59{col 49}{space 3}0.010{col 57}{space 4} .0329868{col 70}{space 3} .2376613
{txt}{space 10}edu92 {c |}{col 17}{res}{space 2}-.0735826{col 29}{space 2} .0532613{col 40}{space 1}   -1.38{col 49}{space 3}0.167{col 57}{space 4}-.1779728{col 70}{space 3} .0308076
{txt}{space 10}age92 {c |}{col 17}{res}{space 2}-.0775639{col 29}{space 2} .0466772{col 40}{space 1}   -1.66{col 49}{space 3}0.097{col 57}{space 4}-.1690495{col 70}{space 3} .0139216
{txt}{space 7}income92 {c |}{col 17}{res}{space 2} .0118012{col 29}{space 2} .0503028{col 40}{space 1}    0.23{col 49}{space 3}0.815{col 57}{space 4}-.0867905{col 70}{space 3} .1103928
{txt}{space 7}female92 {c |}{col 17}{res}{space 2} .0010301{col 29}{space 2} .0460291{col 40}{space 1}    0.02{col 49}{space 3}0.982{col 57}{space 4}-.0891853{col 70}{space 3} .0912454
{txt}{space 8}black92 {c |}{col 17}{res}{space 2}-.0139863{col 29}{space 2} .0453425{col 40}{space 1}   -0.31{col 49}{space 3}0.758{col 57}{space 4}-.1028561{col 70}{space 3} .0748834
{txt}{space 8}south92 {c |}{col 17}{res}{space 2} .0161863{col 29}{space 2} .0454263{col 40}{space 1}    0.36{col 49}{space 3}0.722{col 57}{space 4}-.0728476{col 70}{space 3} .1052203
{txt}{space 10}_cons {c |}{col 17}{res}{space 2}  1.20407{col 29}{space 2} .2425271{col 40}{space 1}    4.96{col 49}{space 3}0.000{col 57}{space 4} .7287258{col 70}{space 3} 1.679415
{space 2}{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}affectpol96  {col 17}{c |}
{space 9}ppol92 {c |}{col 17}{res}{space 2} .0954894{col 29}{space 2} .0464728{col 40}{space 1}    2.05{col 49}{space 3}0.040{col 57}{space 4} .0044044{col 70}{space 3} .1865745
{txt}{space 4}affectpol92 {c |}{col 17}{res}{space 2} .4926537{col 29}{space 2} .0434772{col 40}{space 1}   11.33{col 49}{space 3}0.000{col 57}{space 4}   .40744{col 70}{space 3} .5778674
{txt}{space 2}pidstrength92 {c |}{col 17}{res}{space 2} .0096872{col 29}{space 2} .0440358{col 40}{space 1}    0.22{col 49}{space 3}0.826{col 57}{space 4}-.0766214{col 70}{space 3} .0959959
{txt}{space 2}ideostreng~92 {c |}{col 17}{res}{space 2} .0872562{col 29}{space 2} .0435133{col 40}{space 1}    2.01{col 49}{space 3}0.045{col 57}{space 4} .0019717{col 70}{space 3} .1725408
{txt}{space 5}interest92 {c |}{col 17}{res}{space 2} .0406593{col 29}{space 2} .0432375{col 40}{space 1}    0.94{col 49}{space 3}0.347{col 57}{space 4}-.0440846{col 70}{space 3} .1254032
{txt}{space 9}info92 {c |}{col 17}{res}{space 2}-.0053545{col 29}{space 2} .0482344{col 40}{space 1}   -0.11{col 49}{space 3}0.912{col 57}{space 4}-.0998922{col 70}{space 3} .0891831
{txt}{space 10}edu92 {c |}{col 17}{res}{space 2}-.0792754{col 29}{space 2} .0487479{col 40}{space 1}   -1.63{col 49}{space 3}0.104{col 57}{space 4}-.1748195{col 70}{space 3} .0162687
{txt}{space 10}age92 {c |}{col 17}{res}{space 2}-.0409034{col 29}{space 2} .0428508{col 40}{space 1}   -0.95{col 49}{space 3}0.340{col 57}{space 4}-.1248894{col 70}{space 3} .0430825
{txt}{space 7}income92 {c |}{col 17}{res}{space 2} .0645138{col 29}{space 2} .0459585{col 40}{space 1}    1.40{col 49}{space 3}0.160{col 57}{space 4}-.0255632{col 70}{space 3} .1545907
{txt}{space 7}female92 {c |}{col 17}{res}{space 2} .0046513{col 29}{space 2} .0421398{col 40}{space 1}    0.11{col 49}{space 3}0.912{col 57}{space 4}-.0779413{col 70}{space 3} .0872439
{txt}{space 8}black92 {c |}{col 17}{res}{space 2}-.0295843{col 29}{space 2} .0414943{col 40}{space 1}   -0.71{col 49}{space 3}0.476{col 57}{space 4}-.1109116{col 70}{space 3} .0517431
{txt}{space 8}south92 {c |}{col 17}{res}{space 2}-.0522735{col 29}{space 2} .0415245{col 40}{space 1}   -1.26{col 49}{space 3}0.208{col 57}{space 4}-.1336599{col 70}{space 3}  .029113
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .5841522{col 29}{space 2} .2148111{col 40}{space 1}    2.72{col 49}{space 3}0.007{col 57}{space 4} .1631301{col 70}{space 3} 1.005174
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}var(e.ppol96){c |}{col 17}{res}{space 2}  .774354{col 29}{space 2} .0347771{col 57}{space 4}  .709106{col 70}{space 3} .8456058
{txt}var(e.affect~96){c |}{col 17}{res}{space 2} .6490394{col 29}{space 2} .0350458{col 57}{space 4} .5838608{col 70}{space 3} .7214942
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
LR test of model vs. saturated: chi2({res:1})   = {res:   105.73}, Prob > chi2 = {res}0.0000
{txt}
{com}.         
. mrobust reg ppol96 affectpol92 ppol92 pidstrength92 ideostrength92 ///
>         issextreme92 interest92 info92 edu92 age92 income92 female92 ///
>         black92 south92 if rep96 != .
{res}{txt}note:  sample size varies across model specifications.
Listwise deletion:  153 out of 549 observations will not be used.

Calculating 4,096  models...
Estimated time is 66 seconds (1.1 minutes).
Each dot represents 1000 models calculated
....{res}
{txt}Linear regression;
Variable of interest {col 29}{res}affectpol92
{txt}Outcome variable  {col 29}{res}ppol96{col 46}{txt}Number of observations{col 70}{res}      396
{txt}Possible control terms   {col 29}{res}12{col 46}{txt}Mean R-squared{col 70}{res}     0.19
{txt}Number of models{col 29}{res}4,096          {col 46}{txt}Multicollinearity{col 70}{res}     0.36
{txt}{hline 79}
Model Robustness Statistics:{col 46}Significance Testing:

Mean(b){col 19}{res}   0.1945{col 46}{txt}Sign Stability{col 70}{res}      100%
{txt}Sampling SE{col 19}{res}   0.0444{col 46}{txt}Significance rate{col 70}{res}      100%
{txt}Modeling SE{col 19}{res}   0.0589{col 46}{txt}{hline 34}
Total SE{col 19}{res}   0.0737{col 46}{txt}Positive{col 70}{res}      100%
{txt}{hline 30}{col 46}Positive and Sig{col 70}{res}      100%
{txt}Robustness Ratio:{col 19}{res}   2.6372{col 46}{txt}Negative{col 70}{res}        0%
{txt}{col 46}Negative and Sig{col 70}{res}        0%
{txt}{hline 79}
Model Influence
{col 29}Marginal Effect{col 55}Percent Change
{col 26}of Variable Inclusion{col 56}From Mean(b)
{res}{txt}ppol92{col 29}{res}  -0.1109{col 55}    -57.0{txt}%
{res}{txt}issextreme92{col 29}{res}  -0.0311{col 55}    -16.0{txt}%
{res}{txt}info92{col 29}{res}  -0.0159{col 55}     -8.2{txt}%
{res}{txt}pidstrength92{col 29}{res}  -0.0141{col 55}     -7.2{txt}%
{res}{txt}interest92{col 29}{res}   0.0037{col 55}      1.9{txt}%
{res}{txt}ideostrength92{col 29}{res}   0.0031{col 55}      1.6{txt}%
{res}{txt}age92{col 29}{res}  -0.0022{col 55}     -1.1{txt}%
{res}{txt}edu92{col 29}{res}   0.0007{col 55}      0.3{txt}%
{res}{txt}black92{col 29}{res}  -0.0003{col 55}     -0.2{txt}%
{res}{txt}female92{col 29}{res}   0.0003{col 55}      0.1{txt}%
{res}{txt}income92{col 29}{res}  -0.0001{col 55}     -0.1{txt}%
{res}{txt}south92{col 29}{res}  -0.0001{col 55}     -0.1{txt}%

Constant{col 29}{res}   0.2779
{txt}R-squared{col 29}{res}   0.9922
{txt}{hline 79}

This command took {res}54.9{txt} seconds ({res}.9{txt} minutes) to complete.
{res}{txt}
{com}.         
. mrobust reg affectpol96 ppol92 affectpol92 pidstrength92 ideostrength92 ///
>         issextreme92 interest92 info92 edu92 age92 income92 female92  ///
>         black92 south92 if rep96 != .
{res}{txt}note:  sample size varies across model specifications.
Listwise deletion:  151 out of 549 observations will not be used.

Calculating 4,096  models...
Estimated time is 64 seconds (1.1 minutes).
Each dot represents 1000 models calculated
....{res}
{txt}Linear regression;
Variable of interest {col 29}{res}ppol92
{txt}Outcome variable  {col 29}{res}affectpol96{col 46}{txt}Number of observations{col 70}{res}      398
{txt}Possible control terms   {col 29}{res}12{col 46}{txt}Mean R-squared{col 70}{res}     0.26
{txt}Number of models{col 29}{res}4,096          {col 46}{txt}Multicollinearity{col 70}{res}     0.25
{txt}{hline 79}
Model Robustness Statistics:{col 46}Significance Testing:

Mean(b){col 19}{res}   0.2052{col 46}{txt}Sign Stability{col 70}{res}      100%
{txt}Sampling SE{col 19}{res}   0.0535{col 46}{txt}Significance rate{col 70}{res}       76%
{txt}Modeling SE{col 19}{res}   0.1034{col 46}{txt}{hline 34}
Total SE{col 19}{res}   0.1164{col 46}{txt}Positive{col 70}{res}      100%
{txt}{hline 30}{col 46}Positive and Sig{col 70}{res}       76%
{txt}Robustness Ratio:{col 19}{res}   1.7623{col 46}{txt}Negative{col 70}{res}        0%
{txt}{col 46}Negative and Sig{col 70}{res}        0%
{txt}{hline 79}
Model Influence
{col 29}Marginal Effect{col 55}Percent Change
{col 26}of Variable Inclusion{col 56}From Mean(b)
{res}{txt}affectpol92{col 29}{res}  -0.2035{col 55}    -99.2{txt}%
{res}{txt}ideostrength92{col 29}{res}  -0.0155{col 55}     -7.6{txt}%
{res}{txt}issextreme92{col 29}{res}  -0.0146{col 55}     -7.1{txt}%
{res}{txt}pidstrength92{col 29}{res}  -0.0133{col 55}     -6.5{txt}%
{res}{txt}interest92{col 29}{res}  -0.0085{col 55}     -4.1{txt}%
{res}{txt}info92{col 29}{res}  -0.0057{col 55}     -2.8{txt}%
{res}{txt}edu92{col 29}{res}   0.0046{col 55}      2.2{txt}%
{res}{txt}age92{col 29}{res}  -0.0028{col 55}     -1.4{txt}%
{res}{txt}income92{col 29}{res}  -0.0025{col 55}     -1.2{txt}%
{res}{txt}black92{col 29}{res}   0.0020{col 55}      1.0{txt}%
{res}{txt}female92{col 29}{res}  -0.0012{col 55}     -0.6{txt}%
{res}{txt}south92{col 29}{res}  -0.0001{col 55}     -0.1{txt}%

Constant{col 29}{res}   0.3357
{txt}R-squared{col 29}{res}   0.9863
{txt}{hline 79}

This command took {res}55{txt} seconds ({res}.9{txt} minutes) to complete.
{res}{txt}
{com}. 
.         
. * Disagregating affective polarization scales
. sem (ppol96 <- ppol92 partydifftherm92 pidstrength92 ideostrength92 ///
>         interest92 info92 edu92 age92 income92 female92 ///
>         black92 south92) ///
>         (partydifftherm96 <- partydifftherm92 ppol92 pidstrength92 ideostrength92   ///
>         interest92 info92 edu92 age92 income92 female92  ///
>         black92 south92) if rep96 != ., standardized
{res}{txt}(156 observations with missing values excluded)

Endogenous variables

{p 0 11 2}Observed:{space 2}{res}ppol96 partydifftherm96{p_end}
{txt}
Exogenous variables

{p 0 11 2}Observed:{space 2}{res}ppol92 partydifftherm92 pidstrength92 ideostrength92 interest92 info92 edu92 age92 income92 female92 black92 south92{p_end}
{txt}
Fitting target model:

Iteration 0:{space 3}log likelihood = {res:-3991.2329}  
Iteration 1:{space 3}log likelihood = {res:-3991.2329}  

{col 1}Structural equation model{col 49}Number of obs{col 67}= {res}       393
{txt}{col 1}Estimation method{col 20}= {res}ml
{txt}{col 1}Log likelihood{col 20}= {res}-3991.2329

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}      OIM
{col 1}   Standardized{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}Structural     {col 17}{txt}{c |}
{space 2}{col 3}ppol96       {col 17}{c |}
{space 9}ppol92 {c |}{col 17}{res}{space 2} .3531555{col 29}{space 2} .0468669{col 40}{space 1}    7.54{col 49}{space 3}0.000{col 57}{space 4} .2612981{col 70}{space 3} .4450129
{txt}{space 2}partydifft~92 {c |}{col 17}{res}{space 2} .1418347{col 29}{space 2} .0516128{col 40}{space 1}    2.75{col 49}{space 3}0.006{col 57}{space 4} .0406755{col 70}{space 3} .2429939
{txt}{space 2}pidstrength92 {c |}{col 17}{res}{space 2} .0336468{col 29}{space 2} .0491005{col 40}{space 1}    0.69{col 49}{space 3}0.493{col 57}{space 4}-.0625884{col 70}{space 3} .1298821
{txt}{space 2}ideostreng~92 {c |}{col 17}{res}{space 2} .0001677{col 29}{space 2} .0462746{col 40}{space 1}    0.00{col 49}{space 3}0.997{col 57}{space 4}-.0905288{col 70}{space 3} .0908643
{txt}{space 5}interest92 {c |}{col 17}{res}{space 2}-.0551332{col 29}{space 2} .0473237{col 40}{space 1}   -1.17{col 49}{space 3}0.244{col 57}{space 4} -.147886{col 70}{space 3} .0376197
{txt}{space 9}info92 {c |}{col 17}{res}{space 2} .1438847{col 29}{space 2} .0523318{col 40}{space 1}    2.75{col 49}{space 3}0.006{col 57}{space 4} .0413163{col 70}{space 3} .2464532
{txt}{space 10}edu92 {c |}{col 17}{res}{space 2}-.0736023{col 29}{space 2} .0539818{col 40}{space 1}   -1.36{col 49}{space 3}0.173{col 57}{space 4}-.1794048{col 70}{space 3} .0322001
{txt}{space 10}age92 {c |}{col 17}{res}{space 2}-.0809489{col 29}{space 2} .0470141{col 40}{space 1}   -1.72{col 49}{space 3}0.085{col 57}{space 4}-.1730949{col 70}{space 3} .0111971
{txt}{space 7}income92 {c |}{col 17}{res}{space 2} .0282364{col 29}{space 2} .0511297{col 40}{space 1}    0.55{col 49}{space 3}0.581{col 57}{space 4}-.0719759{col 70}{space 3} .1284488
{txt}{space 7}female92 {c |}{col 17}{res}{space 2} .0163689{col 29}{space 2} .0462263{col 40}{space 1}    0.35{col 49}{space 3}0.723{col 57}{space 4}-.0742331{col 70}{space 3} .1069709
{txt}{space 8}black92 {c |}{col 17}{res}{space 2}-.0332323{col 29}{space 2} .0459624{col 40}{space 1}   -0.72{col 49}{space 3}0.470{col 57}{space 4}-.1233171{col 70}{space 3} .0568524
{txt}{space 8}south92 {c |}{col 17}{res}{space 2} .0121227{col 29}{space 2} .0455187{col 40}{space 1}    0.27{col 49}{space 3}0.790{col 57}{space 4}-.0770924{col 70}{space 3} .1013377
{txt}{space 10}_cons {c |}{col 17}{res}{space 2}  1.15274{col 29}{space 2} .2446563{col 40}{space 1}    4.71{col 49}{space 3}0.000{col 57}{space 4} .6732222{col 70}{space 3} 1.632257
{space 2}{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}partydifft~96{col 17}{c |}
{space 9}ppol92 {c |}{col 17}{res}{space 2} .1205781{col 29}{space 2} .0495121{col 40}{space 1}    2.44{col 49}{space 3}0.015{col 57}{space 4} .0235362{col 70}{space 3} .2176201
{txt}{space 2}partydifft~92 {c |}{col 17}{res}{space 2} .3756931{col 29}{space 2} .0478882{col 40}{space 1}    7.85{col 49}{space 3}0.000{col 57}{space 4} .2818339{col 70}{space 3} .4695523
{txt}{space 2}pidstrength92 {c |}{col 17}{res}{space 2} .0394166{col 29}{space 2} .0486388{col 40}{space 1}    0.81{col 49}{space 3}0.418{col 57}{space 4}-.0559138{col 70}{space 3}  .134747
{txt}{space 2}ideostreng~92 {c |}{col 17}{res}{space 2} .0928848{col 29}{space 2}  .045599{col 40}{space 1}    2.04{col 49}{space 3}0.042{col 57}{space 4} .0035123{col 70}{space 3} .1822573
{txt}{space 5}interest92 {c |}{col 17}{res}{space 2} .0761109{col 29}{space 2}  .046812{col 40}{space 1}    1.63{col 49}{space 3}0.104{col 57}{space 4}-.0156388{col 70}{space 3} .1678606
{txt}{space 9}info92 {c |}{col 17}{res}{space 2} -.042586{col 29}{space 2} .0523373{col 40}{space 1}   -0.81{col 49}{space 3}0.416{col 57}{space 4}-.1451652{col 70}{space 3} .0599931
{txt}{space 10}edu92 {c |}{col 17}{res}{space 2}-.1030726{col 29}{space 2} .0533577{col 40}{space 1}   -1.93{col 49}{space 3}0.053{col 57}{space 4}-.2076518{col 70}{space 3} .0015066
{txt}{space 10}age92 {c |}{col 17}{res}{space 2}-.0206729{col 29}{space 2} .0467586{col 40}{space 1}   -0.44{col 49}{space 3}0.658{col 57}{space 4}-.1123182{col 70}{space 3} .0709723
{txt}{space 7}income92 {c |}{col 17}{res}{space 2} .0645309{col 29}{space 2} .0505723{col 40}{space 1}    1.28{col 49}{space 3}0.202{col 57}{space 4} -.034589{col 70}{space 3} .1636509
{txt}{space 7}female92 {c |}{col 17}{res}{space 2} .0262557{col 29}{space 2} .0457902{col 40}{space 1}    0.57{col 49}{space 3}0.566{col 57}{space 4}-.0634914{col 70}{space 3} .1160029
{txt}{space 8}black92 {c |}{col 17}{res}{space 2}-.0352165{col 29}{space 2} .0455371{col 40}{space 1}   -0.77{col 49}{space 3}0.439{col 57}{space 4}-.1244676{col 70}{space 3} .0540346
{txt}{space 8}south92 {c |}{col 17}{res}{space 2}-.0477381{col 29}{space 2} .0450383{col 40}{space 1}   -1.06{col 49}{space 3}0.289{col 57}{space 4}-.1360116{col 70}{space 3} .0405354
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .4881067{col 29}{space 2} .2328423{col 40}{space 1}    2.10{col 49}{space 3}0.036{col 57}{space 4} .0317441{col 70}{space 3} .9444692
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}var(e.ppol96){c |}{col 17}{res}{space 2} .7727131{col 29}{space 2}   .03499{col 57}{space 4} .7070892{col 70}{space 3} .8444274
{txt}var(e.partyd~96){c |}{col 17}{res}{space 2}  .758605{col 29}{space 2}   .03526{col 57}{space 4} .6925511{col 70}{space 3} .8309591
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
LR test of model vs. saturated: chi2({res:1})   = {res:    89.60}, Prob > chi2 = {res}0.0000
{txt}
{com}.         
. sem (ppol96 <- ppol92 diffideotherm92 pidstrength92 ideostrength92 ///
>         interest92 info92 edu92 age92 income92 female92 ///
>         black92 south92) ///
>         (diffideotherm96 <- diffideotherm92 ppol92 pidstrength92 ideostrength92   ///
>         interest92 info92 edu92 age92 income92 female92  ///
>         black92 south92) if rep96 != ., standardized    
{res}{txt}(194 observations with missing values excluded)

Endogenous variables

{p 0 11 2}Observed:{space 2}{res}ppol96 diffideotherm96{p_end}
{txt}
Exogenous variables

{p 0 11 2}Observed:{space 2}{res}ppol92 diffideotherm92 pidstrength92 ideostrength92 interest92 info92 edu92 age92 income92 female92 black92 south92{p_end}
{txt}
Fitting target model:

Iteration 0:{space 3}log likelihood = {res:-3530.7195}  
Iteration 1:{space 3}log likelihood = {res:-3530.7195}  

{col 1}Structural equation model{col 49}Number of obs{col 67}= {res}       355
{txt}{col 1}Estimation method{col 20}= {res}ml
{txt}{col 1}Log likelihood{col 20}= {res}-3530.7195

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}      OIM
{col 1}   Standardized{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}Structural     {col 17}{txt}{c |}
{space 2}{col 3}ppol96       {col 17}{c |}
{space 9}ppol92 {c |}{col 17}{res}{space 2} .4153255{col 29}{space 2} .0432138{col 40}{space 1}    9.61{col 49}{space 3}0.000{col 57}{space 4}  .330628{col 70}{space 3} .5000229
{txt}{space 2}diffideoth~92 {c |}{col 17}{res}{space 2} .1442118{col 29}{space 2} .0521451{col 40}{space 1}    2.77{col 49}{space 3}0.006{col 57}{space 4} .0420093{col 70}{space 3} .2464142
{txt}{space 2}pidstrength92 {c |}{col 17}{res}{space 2}  .073367{col 29}{space 2} .0469928{col 40}{space 1}    1.56{col 49}{space 3}0.118{col 57}{space 4}-.0187372{col 70}{space 3} .1654713
{txt}{space 2}ideostreng~92 {c |}{col 17}{res}{space 2}-.0349451{col 29}{space 2} .0504379{col 40}{space 1}   -0.69{col 49}{space 3}0.488{col 57}{space 4}-.1338015{col 70}{space 3} .0639113
{txt}{space 5}interest92 {c |}{col 17}{res}{space 2}-.0822508{col 29}{space 2} .0474966{col 40}{space 1}   -1.73{col 49}{space 3}0.083{col 57}{space 4}-.1753424{col 70}{space 3} .0108407
{txt}{space 9}info92 {c |}{col 17}{res}{space 2} .2080191{col 29}{space 2} .0505381{col 40}{space 1}    4.12{col 49}{space 3}0.000{col 57}{space 4} .1089663{col 70}{space 3} .3070719
{txt}{space 10}edu92 {c |}{col 17}{res}{space 2}-.0633221{col 29}{space 2} .0519648{col 40}{space 1}   -1.22{col 49}{space 3}0.223{col 57}{space 4}-.1651712{col 70}{space 3} .0385269
{txt}{space 10}age92 {c |}{col 17}{res}{space 2} -.092758{col 29}{space 2} .0468933{col 40}{space 1}   -1.98{col 49}{space 3}0.048{col 57}{space 4}-.1846672{col 70}{space 3}-.0008489
{txt}{space 7}income92 {c |}{col 17}{res}{space 2}  .022495{col 29}{space 2} .0497185{col 40}{space 1}    0.45{col 49}{space 3}0.651{col 57}{space 4}-.0749515{col 70}{space 3} .1199415
{txt}{space 7}female92 {c |}{col 17}{res}{space 2} .0225842{col 29}{space 2} .0460309{col 40}{space 1}    0.49{col 49}{space 3}0.624{col 57}{space 4}-.0676348{col 70}{space 3} .1128032
{txt}{space 8}black92 {c |}{col 17}{res}{space 2} .0409131{col 29}{space 2} .0460084{col 40}{space 1}    0.89{col 49}{space 3}0.374{col 57}{space 4}-.0492617{col 70}{space 3}  .131088
{txt}{space 8}south92 {c |}{col 17}{res}{space 2} .0230749{col 29}{space 2} .0457795{col 40}{space 1}    0.50{col 49}{space 3}0.614{col 57}{space 4}-.0666512{col 70}{space 3} .1128011
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .8145734{col 29}{space 2} .2507232{col 40}{space 1}    3.25{col 49}{space 3}0.001{col 57}{space 4} .3231649{col 70}{space 3} 1.305982
{space 2}{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}diffideoth~96{col 17}{c |}
{space 9}ppol92 {c |}{col 17}{res}{space 2} .0720305{col 29}{space 2} .0466885{col 40}{space 1}    1.54{col 49}{space 3}0.123{col 57}{space 4}-.0194773{col 70}{space 3} .1635383
{txt}{space 2}diffideoth~92 {c |}{col 17}{res}{space 2} .4783023{col 29}{space 2} .0453197{col 40}{space 1}   10.55{col 49}{space 3}0.000{col 57}{space 4} .3894773{col 70}{space 3} .5671274
{txt}{space 2}pidstrength92 {c |}{col 17}{res}{space 2} .0445568{col 29}{space 2} .0457362{col 40}{space 1}    0.97{col 49}{space 3}0.330{col 57}{space 4}-.0450845{col 70}{space 3}  .134198
{txt}{space 2}ideostreng~92 {c |}{col 17}{res}{space 2} .0828298{col 29}{space 2} .0488471{col 40}{space 1}    1.70{col 49}{space 3}0.090{col 57}{space 4}-.0129088{col 70}{space 3} .1785684
{txt}{space 5}interest92 {c |}{col 17}{res}{space 2}-.0408946{col 29}{space 2} .0462701{col 40}{space 1}   -0.88{col 49}{space 3}0.377{col 57}{space 4}-.1315824{col 70}{space 3} .0497931
{txt}{space 9}info92 {c |}{col 17}{res}{space 2} .0136334{col 29}{space 2} .0501704{col 40}{space 1}    0.27{col 49}{space 3}0.786{col 57}{space 4}-.0846988{col 70}{space 3} .1119656
{txt}{space 10}edu92 {c |}{col 17}{res}{space 2} .0848144{col 29}{space 2} .0503953{col 40}{space 1}    1.68{col 49}{space 3}0.092{col 57}{space 4}-.0139587{col 70}{space 3} .1835874
{txt}{space 10}age92 {c |}{col 17}{res}{space 2} .0127218{col 29}{space 2} .0457769{col 40}{space 1}    0.28{col 49}{space 3}0.781{col 57}{space 4}-.0769992{col 70}{space 3} .1024428
{txt}{space 7}income92 {c |}{col 17}{res}{space 2} .0130445{col 29}{space 2} .0482986{col 40}{space 1}    0.27{col 49}{space 3}0.787{col 57}{space 4} -.081619{col 70}{space 3} .1077081
{txt}{space 7}female92 {c |}{col 17}{res}{space 2} .0194499{col 29}{space 2} .0447121{col 40}{space 1}    0.44{col 49}{space 3}0.664{col 57}{space 4}-.0681841{col 70}{space 3}  .107084
{txt}{space 8}black92 {c |}{col 17}{res}{space 2}-.0624909{col 29}{space 2} .0446256{col 40}{space 1}   -1.40{col 49}{space 3}0.161{col 57}{space 4}-.1499553{col 70}{space 3} .0249736
{txt}{space 8}south92 {c |}{col 17}{res}{space 2}-.0159142{col 29}{space 2}  .044472{col 40}{space 1}   -0.36{col 49}{space 3}0.720{col 57}{space 4}-.1030777{col 70}{space 3} .0712493
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .0866909{col 29}{space 2} .2332683{col 40}{space 1}    0.37{col 49}{space 3}0.710{col 57}{space 4}-.3705066{col 70}{space 3} .5438883
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}var(e.ppol96){c |}{col 17}{res}{space 2} .6971333{col 29}{space 2} .0375146{col 57}{space 4} .6273507{col 70}{space 3} .7746781
{txt}var(e.diffid~96){c |}{col 17}{res}{space 2} .6576451{col 29}{space 2} .0371857{col 57}{space 4} .5886558{col 70}{space 3} .7347198
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
LR test of model vs. saturated: chi2({res:1})   = {res:    41.99}, Prob > chi2 = {res}0.0000
{txt}
{com}.         
. sem (ppol96 <- ppol92 diffcandtherm92 pidstrength92 ideostrength92 ///
>         interest92 info92 edu92 age92 income92 female92 ///
>         black92 south92) ///
>         (diffcandtherm96 <- diffcandtherm92 ppol92 pidstrength92 ideostrength92   ///
>         interest92 info92 edu92 age92 income92 female92  ///
>         black92 south92) if rep96 != ., standardized            
{res}{txt}(161 observations with missing values excluded)

Endogenous variables

{p 0 11 2}Observed:{space 2}{res}ppol96 diffcandtherm96{p_end}
{txt}
Exogenous variables

{p 0 11 2}Observed:{space 2}{res}ppol92 diffcandtherm92 pidstrength92 ideostrength92 interest92 info92 edu92 age92 income92 female92 black92 south92{p_end}
{txt}
Fitting target model:

Iteration 0:{space 3}log likelihood = {res:-3918.9457}  
Iteration 1:{space 3}log likelihood = {res:-3918.9457}  

{col 1}Structural equation model{col 49}Number of obs{col 67}= {res}       388
{txt}{col 1}Estimation method{col 20}= {res}ml
{txt}{col 1}Log likelihood{col 20}= {res}-3918.9457

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}      OIM
{col 1}   Standardized{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}Structural     {col 17}{txt}{c |}
{space 2}{col 3}ppol96       {col 17}{c |}
{space 9}ppol92 {c |}{col 17}{res}{space 2} .3933748{col 29}{space 2} .0459409{col 40}{space 1}    8.56{col 49}{space 3}0.000{col 57}{space 4} .3033323{col 70}{space 3} .4834172
{txt}{space 2}diffcandth~92 {c |}{col 17}{res}{space 2} .0805644{col 29}{space 2} .0507936{col 40}{space 1}    1.59{col 49}{space 3}0.113{col 57}{space 4}-.0189891{col 70}{space 3}  .180118
{txt}{space 2}pidstrength92 {c |}{col 17}{res}{space 2} .0660256{col 29}{space 2} .0473664{col 40}{space 1}    1.39{col 49}{space 3}0.163{col 57}{space 4}-.0268109{col 70}{space 3}  .158862
{txt}{space 2}ideostreng~92 {c |}{col 17}{res}{space 2} .0175804{col 29}{space 2} .0463753{col 40}{space 1}    0.38{col 49}{space 3}0.705{col 57}{space 4}-.0733135{col 70}{space 3} .1084744
{txt}{space 5}interest92 {c |}{col 17}{res}{space 2}-.0703417{col 29}{space 2} .0475762{col 40}{space 1}   -1.48{col 49}{space 3}0.139{col 57}{space 4}-.1635894{col 70}{space 3}  .022906
{txt}{space 9}info92 {c |}{col 17}{res}{space 2} .1563334{col 29}{space 2} .0515529{col 40}{space 1}    3.03{col 49}{space 3}0.002{col 57}{space 4} .0552915{col 70}{space 3} .2573752
{txt}{space 10}edu92 {c |}{col 17}{res}{space 2} -.078433{col 29}{space 2} .0524089{col 40}{space 1}   -1.50{col 49}{space 3}0.135{col 57}{space 4}-.1811526{col 70}{space 3} .0242866
{txt}{space 10}age92 {c |}{col 17}{res}{space 2}-.0728169{col 29}{space 2} .0466962{col 40}{space 1}   -1.56{col 49}{space 3}0.119{col 57}{space 4}-.1643398{col 70}{space 3} .0187059
{txt}{space 7}income92 {c |}{col 17}{res}{space 2} .0242995{col 29}{space 2} .0496685{col 40}{space 1}    0.49{col 49}{space 3}0.625{col 57}{space 4}-.0730491{col 70}{space 3}  .121648
{txt}{space 7}female92 {c |}{col 17}{res}{space 2} .0148734{col 29}{space 2} .0464694{col 40}{space 1}    0.32{col 49}{space 3}0.749{col 57}{space 4}-.0762051{col 70}{space 3} .1059518
{txt}{space 8}black92 {c |}{col 17}{res}{space 2}-.0033892{col 29}{space 2} .0453766{col 40}{space 1}   -0.07{col 49}{space 3}0.940{col 57}{space 4}-.0923257{col 70}{space 3} .0855474
{txt}{space 8}south92 {c |}{col 17}{res}{space 2} .0249127{col 29}{space 2} .0453555{col 40}{space 1}    0.55{col 49}{space 3}0.583{col 57}{space 4}-.0639824{col 70}{space 3} .1138079
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 1.030792{col 29}{space 2} .2445488{col 40}{space 1}    4.22{col 49}{space 3}0.000{col 57}{space 4} .5514848{col 70}{space 3} 1.510098
{space 2}{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}diffcandth~96{col 17}{c |}
{space 9}ppol92 {c |}{col 17}{res}{space 2} .1400133{col 29}{space 2} .0498658{col 40}{space 1}    2.81{col 49}{space 3}0.005{col 57}{space 4} .0422782{col 70}{space 3} .2377484
{txt}{space 2}diffcandth~92 {c |}{col 17}{res}{space 2} .3475128{col 29}{space 2} .0478014{col 40}{space 1}    7.27{col 49}{space 3}0.000{col 57}{space 4} .2538238{col 70}{space 3} .4412017
{txt}{space 2}pidstrength92 {c |}{col 17}{res}{space 2} .0095543{col 29}{space 2} .0476149{col 40}{space 1}    0.20{col 49}{space 3}0.841{col 57}{space 4}-.0837692{col 70}{space 3} .1028777
{txt}{space 2}ideostreng~92 {c |}{col 17}{res}{space 2} .0964061{col 29}{space 2} .0462381{col 40}{space 1}    2.08{col 49}{space 3}0.037{col 57}{space 4} .0057811{col 70}{space 3} .1870311
{txt}{space 5}interest92 {c |}{col 17}{res}{space 2} .0671104{col 29}{space 2} .0477165{col 40}{space 1}    1.41{col 49}{space 3}0.160{col 57}{space 4}-.0264123{col 70}{space 3} .1606331
{txt}{space 9}info92 {c |}{col 17}{res}{space 2} .0471825{col 29}{space 2} .0522682{col 40}{space 1}    0.90{col 49}{space 3}0.367{col 57}{space 4}-.0552612{col 70}{space 3} .1496263
{txt}{space 10}edu92 {c |}{col 17}{res}{space 2} -.171384{col 29}{space 2}  .051949{col 40}{space 1}   -3.30{col 49}{space 3}0.001{col 57}{space 4}-.2732021{col 70}{space 3}-.0695659
{txt}{space 10}age92 {c |}{col 17}{res}{space 2}-.0829694{col 29}{space 2} .0467759{col 40}{space 1}   -1.77{col 49}{space 3}0.076{col 57}{space 4}-.1746484{col 70}{space 3} .0087096
{txt}{space 7}income92 {c |}{col 17}{res}{space 2} .0545752{col 29}{space 2} .0497372{col 40}{space 1}    1.10{col 49}{space 3}0.273{col 57}{space 4} -.042908{col 70}{space 3} .1520584
{txt}{space 7}female92 {c |}{col 17}{res}{space 2}-.0498724{col 29}{space 2} .0465286{col 40}{space 1}   -1.07{col 49}{space 3}0.284{col 57}{space 4}-.1410668{col 70}{space 3}  .041322
{txt}{space 8}black92 {c |}{col 17}{res}{space 2} .0090539{col 29}{space 2} .0454965{col 40}{space 1}    0.20{col 49}{space 3}0.842{col 57}{space 4}-.0801177{col 70}{space 3} .0982255
{txt}{space 8}south92 {c |}{col 17}{res}{space 2}-.0375575{col 29}{space 2}  .045454{col 40}{space 1}   -0.83{col 49}{space 3}0.409{col 57}{space 4}-.1266456{col 70}{space 3} .0515306
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .7516964{col 29}{space 2} .2387767{col 40}{space 1}    3.15{col 49}{space 3}0.002{col 57}{space 4} .2837026{col 70}{space 3}  1.21969
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}var(e.ppol96){c |}{col 17}{res}{space 2} .7559105{col 29}{space 2}   .03553{col 57}{space 4} .6893843{col 70}{space 3} .8288564
{txt}var(e.diffca~96){c |}{col 17}{res}{space 2} .7599811{col 29}{space 2} .0354633{col 57}{space 4} .6935581{col 70}{space 3} .8327654
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
LR test of model vs. saturated: chi2({res:1})   = {res:    57.05}, Prob > chi2 = {res}0.0000
{txt}
{com}. 
. sem (ppol96 <- ppol92 diffideotherm92 diffcandtherm92 partydifftherm92 /// 
>         pidstrength92 ideostrength92 issextreme92 ///
>         interest92 info92 edu92 age92 income92 female92 ///
>         black92 south92) ///
>         (diffideotherm96 diffcandtherm96 partydifftherm96 <- diffideotherm92 ///
>         diffcandtherm92 partydifftherm92 ppol92 pidstrength92 ///
>         ideostrength92 issextreme92  ///
>         interest92 info92 edu92 age92 income92 female92  ///
>         black92 south92), standardized
{res}{txt}(227 observations with missing values excluded)

Endogenous variables

{p 0 11 2}Observed:{space 2}{res}ppol96 diffideotherm96 diffcandtherm96 partydifftherm96{p_end}
{txt}
Exogenous variables

{p 0 11 2}Observed:{space 2}{res}ppol92 diffideotherm92 diffcandtherm92 partydifftherm92 pidstrength92 ideostrength92 issextreme92 interest92 info92 edu92 age92 income92 female92 black92 south92{p_end}
{txt}
Fitting target model:

Iteration 0:{space 3}log likelihood = {res:-10553.165}  
Iteration 1:{space 3}log likelihood = {res:-10553.165}  

{col 1}Structural equation model{col 49}Number of obs{col 67}= {res}       370
{txt}{col 1}Estimation method{col 20}= {res}ml
{txt}{col 1}Log likelihood{col 20}= {res}-10553.165

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}      OIM
{col 1}   Standardized{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}Structural     {col 17}{txt}{c |}
{space 2}{col 3}ppol96       {col 17}{c |}
{space 9}ppol92 {c |}{col 17}{res}{space 2} .3894934{col 29}{space 2} .0453738{col 40}{space 1}    8.58{col 49}{space 3}0.000{col 57}{space 4} .3005624{col 70}{space 3} .4784244
{txt}{space 2}diffideoth~92 {c |}{col 17}{res}{space 2} .1128544{col 29}{space 2} .0540715{col 40}{space 1}    2.09{col 49}{space 3}0.037{col 57}{space 4} .0068763{col 70}{space 3} .2188326
{txt}{space 2}diffcandth~92 {c |}{col 17}{res}{space 2}-.0088937{col 29}{space 2}  .059942{col 40}{space 1}   -0.15{col 49}{space 3}0.882{col 57}{space 4}-.1263779{col 70}{space 3} .1085905
{txt}{space 2}partydifft~92 {c |}{col 17}{res}{space 2} .0753263{col 29}{space 2} .0616449{col 40}{space 1}    1.22{col 49}{space 3}0.222{col 57}{space 4}-.0454954{col 70}{space 3} .1961481
{txt}{space 2}pidstrength92 {c |}{col 17}{res}{space 2}  .042434{col 29}{space 2} .0490656{col 40}{space 1}    0.86{col 49}{space 3}0.387{col 57}{space 4}-.0537329{col 70}{space 3} .1386008
{txt}{space 2}ideostreng~92 {c |}{col 17}{res}{space 2}-.0025871{col 29}{space 2} .0494523{col 40}{space 1}   -0.05{col 49}{space 3}0.958{col 57}{space 4}-.0995118{col 70}{space 3} .0943375
{txt}{space 3}issextreme92 {c |}{col 17}{res}{space 2} .1300897{col 29}{space 2}  .045771{col 40}{space 1}    2.84{col 49}{space 3}0.004{col 57}{space 4} .0403802{col 70}{space 3} .2197992
{txt}{space 5}interest92 {c |}{col 17}{res}{space 2}-.0922831{col 29}{space 2} .0468216{col 40}{space 1}   -1.97{col 49}{space 3}0.049{col 57}{space 4}-.1840517{col 70}{space 3}-.0005146
{txt}{space 9}info92 {c |}{col 17}{res}{space 2} .1880936{col 29}{space 2}  .049518{col 40}{space 1}    3.80{col 49}{space 3}0.000{col 57}{space 4} .0910401{col 70}{space 3} .2851471
{txt}{space 10}edu92 {c |}{col 17}{res}{space 2}-.0585122{col 29}{space 2} .0512096{col 40}{space 1}   -1.14{col 49}{space 3}0.253{col 57}{space 4}-.1588811{col 70}{space 3} .0418567
{txt}{space 10}age92 {c |}{col 17}{res}{space 2}-.0955863{col 29}{space 2} .0456576{col 40}{space 1}   -2.09{col 49}{space 3}0.036{col 57}{space 4}-.1850736{col 70}{space 3}-.0060991
{txt}{space 7}income92 {c |}{col 17}{res}{space 2} .0066918{col 29}{space 2} .0491625{col 40}{space 1}    0.14{col 49}{space 3}0.892{col 57}{space 4} -.089665{col 70}{space 3} .1030486
{txt}{space 7}female92 {c |}{col 17}{res}{space 2} .0336535{col 29}{space 2} .0447163{col 40}{space 1}    0.75{col 49}{space 3}0.452{col 57}{space 4}-.0539888{col 70}{space 3} .1212958
{txt}{space 8}black92 {c |}{col 17}{res}{space 2} .0190892{col 29}{space 2} .0452108{col 40}{space 1}    0.42{col 49}{space 3}0.673{col 57}{space 4}-.0695223{col 70}{space 3} .1077008
{txt}{space 8}south92 {c |}{col 17}{res}{space 2} .0182331{col 29}{space 2}  .044494{col 40}{space 1}    0.41{col 49}{space 3}0.682{col 57}{space 4}-.0689734{col 70}{space 3} .1054397
{txt}{space 10}_cons {c |}{col 17}{res}{space 2}  .628805{col 29}{space 2}  .247288{col 40}{space 1}    2.54{col 49}{space 3}0.011{col 57}{space 4} .1441293{col 70}{space 3} 1.113481
{space 2}{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}diffideoth~96{col 17}{c |}
{space 9}ppol92 {c |}{col 17}{res}{space 2} .0294436{col 29}{space 2} .0483481{col 40}{space 1}    0.61{col 49}{space 3}0.543{col 57}{space 4}-.0653169{col 70}{space 3} .1242042
{txt}{space 2}diffideoth~92 {c |}{col 17}{res}{space 2} .4248278{col 29}{space 2} .0492096{col 40}{space 1}    8.63{col 49}{space 3}0.000{col 57}{space 4} .3283789{col 70}{space 3} .5212768
{txt}{space 2}diffcandth~92 {c |}{col 17}{res}{space 2} .0602379{col 29}{space 2} .0587324{col 40}{space 1}    1.03{col 49}{space 3}0.305{col 57}{space 4}-.0548756{col 70}{space 3} .1753513
{txt}{space 2}partydifft~92 {c |}{col 17}{res}{space 2} .0704633{col 29}{space 2} .0604883{col 40}{space 1}    1.16{col 49}{space 3}0.244{col 57}{space 4}-.0480916{col 70}{space 3} .1890182
{txt}{space 2}pidstrength92 {c |}{col 17}{res}{space 2} .0151022{col 29}{space 2} .0481719{col 40}{space 1}    0.31{col 49}{space 3}0.754{col 57}{space 4}-.0793131{col 70}{space 3} .1095174
{txt}{space 2}ideostreng~92 {c |}{col 17}{res}{space 2} .0891676{col 29}{space 2} .0483207{col 40}{space 1}    1.85{col 49}{space 3}0.065{col 57}{space 4}-.0055393{col 70}{space 3} .1838744
{txt}{space 3}issextreme92 {c |}{col 17}{res}{space 2} .0277629{col 29}{space 2} .0453243{col 40}{space 1}    0.61{col 49}{space 3}0.540{col 57}{space 4}-.0610711{col 70}{space 3} .1165969
{txt}{space 5}interest92 {c |}{col 17}{res}{space 2} -.049737{col 29}{space 2} .0460876{col 40}{space 1}   -1.08{col 49}{space 3}0.281{col 57}{space 4} -.140067{col 70}{space 3} .0405929
{txt}{space 9}info92 {c |}{col 17}{res}{space 2} .0164815{col 29}{space 2} .0494232{col 40}{space 1}    0.33{col 49}{space 3}0.739{col 57}{space 4}-.0803862{col 70}{space 3} .1133491
{txt}{space 10}edu92 {c |}{col 17}{res}{space 2} .0864715{col 29}{space 2} .0501428{col 40}{space 1}    1.72{col 49}{space 3}0.085{col 57}{space 4}-.0118066{col 70}{space 3} .1847497
{txt}{space 10}age92 {c |}{col 17}{res}{space 2}  .021202{col 29}{space 2} .0450186{col 40}{space 1}    0.47{col 49}{space 3}0.638{col 57}{space 4}-.0670329{col 70}{space 3} .1094368
{txt}{space 7}income92 {c |}{col 17}{res}{space 2} .0468539{col 29}{space 2} .0481762{col 40}{space 1}    0.97{col 49}{space 3}0.331{col 57}{space 4}-.0475698{col 70}{space 3} .1412775
{txt}{space 7}female92 {c |}{col 17}{res}{space 2} .0107836{col 29}{space 2}  .043894{col 40}{space 1}    0.25{col 49}{space 3}0.806{col 57}{space 4} -.075247{col 70}{space 3} .0968142
{txt}{space 8}black92 {c |}{col 17}{res}{space 2}-.0655835{col 29}{space 2} .0442479{col 40}{space 1}   -1.48{col 49}{space 3}0.138{col 57}{space 4}-.1523077{col 70}{space 3} .0211408
{txt}{space 8}south92 {c |}{col 17}{res}{space 2}-.0029324{col 29}{space 2} .0436573{col 40}{space 1}   -0.07{col 49}{space 3}0.946{col 57}{space 4}-.0884991{col 70}{space 3} .0826343
{txt}{space 10}_cons {c |}{col 17}{res}{space 2}-.0344603{col 29}{space 2} .2340352{col 40}{space 1}   -0.15{col 49}{space 3}0.883{col 57}{space 4}-.4931609{col 70}{space 3} .4242403
{space 2}{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}diffcandth~96{col 17}{c |}
{space 9}ppol92 {c |}{col 17}{res}{space 2}  .119017{col 29}{space 2} .0507271{col 40}{space 1}    2.35{col 49}{space 3}0.019{col 57}{space 4} .0195936{col 70}{space 3} .2184403
{txt}{space 2}diffideoth~92 {c |}{col 17}{res}{space 2} .1172726{col 29}{space 2} .0560097{col 40}{space 1}    2.09{col 49}{space 3}0.036{col 57}{space 4} .0074955{col 70}{space 3} .2270496
{txt}{space 2}diffcandth~92 {c |}{col 17}{res}{space 2} .2172362{col 29}{space 2} .0610971{col 40}{space 1}    3.56{col 49}{space 3}0.000{col 57}{space 4} .0974881{col 70}{space 3} .3369844
{txt}{space 2}partydifft~92 {c |}{col 17}{res}{space 2} .1033916{col 29}{space 2} .0637811{col 40}{space 1}    1.62{col 49}{space 3}0.105{col 57}{space 4} -.021617{col 70}{space 3} .2284002
{txt}{space 2}pidstrength92 {c |}{col 17}{res}{space 2} .0028646{col 29}{space 2} .0508981{col 40}{space 1}    0.06{col 49}{space 3}0.955{col 57}{space 4}-.0968938{col 70}{space 3}  .102623
{txt}{space 2}ideostreng~92 {c |}{col 17}{res}{space 2} .0739634{col 29}{space 2}  .051109{col 40}{space 1}    1.45{col 49}{space 3}0.148{col 57}{space 4}-.0262084{col 70}{space 3} .1741352
{txt}{space 3}issextreme92 {c |}{col 17}{res}{space 2} .0692609{col 29}{space 2} .0477703{col 40}{space 1}    1.45{col 49}{space 3}0.147{col 57}{space 4}-.0243672{col 70}{space 3} .1628891
{txt}{space 5}interest92 {c |}{col 17}{res}{space 2} .0482385{col 29}{space 2} .0486925{col 40}{space 1}    0.99{col 49}{space 3}0.322{col 57}{space 4}-.0471971{col 70}{space 3}  .143674
{txt}{space 9}info92 {c |}{col 17}{res}{space 2} .0764165{col 29}{space 2} .0520708{col 40}{space 1}    1.47{col 49}{space 3}0.142{col 57}{space 4}-.0256404{col 70}{space 3} .1784733
{txt}{space 10}edu92 {c |}{col 17}{res}{space 2}-.1293288{col 29}{space 2} .0527344{col 40}{space 1}   -2.45{col 49}{space 3}0.014{col 57}{space 4}-.2326863{col 70}{space 3}-.0259713
{txt}{space 10}age92 {c |}{col 17}{res}{space 2}-.0932315{col 29}{space 2} .0473274{col 40}{space 1}   -1.97{col 49}{space 3}0.049{col 57}{space 4}-.1859915{col 70}{space 3}-.0004715
{txt}{space 7}income92 {c |}{col 17}{res}{space 2} .0890779{col 29}{space 2} .0507437{col 40}{space 1}    1.76{col 49}{space 3}0.079{col 57}{space 4} -.010378{col 70}{space 3} .1885337
{txt}{space 7}female92 {c |}{col 17}{res}{space 2}-.0034539{col 29}{space 2} .0463758{col 40}{space 1}   -0.07{col 49}{space 3}0.941{col 57}{space 4}-.0943488{col 70}{space 3}  .087441
{txt}{space 8}black92 {c |}{col 17}{res}{space 2} .0105689{col 29}{space 2} .0468635{col 40}{space 1}    0.23{col 49}{space 3}0.822{col 57}{space 4}-.0812819{col 70}{space 3} .1024198
{txt}{space 8}south92 {c |}{col 17}{res}{space 2}-.0577755{col 29}{space 2} .0460258{col 40}{space 1}   -1.26{col 49}{space 3}0.209{col 57}{space 4}-.1479844{col 70}{space 3} .0324334
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .3456908{col 29}{space 2} .2511976{col 40}{space 1}    1.38{col 49}{space 3}0.169{col 57}{space 4}-.1466474{col 70}{space 3}  .838029
{space 2}{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}partydifft~96{col 17}{c |}
{space 9}ppol92 {c |}{col 17}{res}{space 2} .1185085{col 29}{space 2} .0492806{col 40}{space 1}    2.40{col 49}{space 3}0.016{col 57}{space 4} .0219202{col 70}{space 3} .2150968
{txt}{space 2}diffideoth~92 {c |}{col 17}{res}{space 2} .0684937{col 29}{space 2} .0546154{col 40}{space 1}    1.25{col 49}{space 3}0.210{col 57}{space 4}-.0385506{col 70}{space 3} .1755379
{txt}{space 2}diffcandth~92 {c |}{col 17}{res}{space 2} .1217017{col 29}{space 2} .0600366{col 40}{space 1}    2.03{col 49}{space 3}0.043{col 57}{space 4} .0040321{col 70}{space 3} .2393713
{txt}{space 2}partydifft~92 {c |}{col 17}{res}{space 2} .2730681{col 29}{space 2} .0606549{col 40}{space 1}    4.50{col 49}{space 3}0.000{col 57}{space 4} .1541867{col 70}{space 3} .3919496
{txt}{space 2}pidstrength92 {c |}{col 17}{res}{space 2} .0568813{col 29}{space 2} .0493566{col 40}{space 1}    1.15{col 49}{space 3}0.249{col 57}{space 4}-.0398559{col 70}{space 3} .1536185
{txt}{space 2}ideostreng~92 {c |}{col 17}{res}{space 2} .0600579{col 29}{space 2} .0496919{col 40}{space 1}    1.21{col 49}{space 3}0.227{col 57}{space 4}-.0373366{col 70}{space 3} .1574523
{txt}{space 3}issextreme92 {c |}{col 17}{res}{space 2} .0866835{col 29}{space 2}  .046329{col 40}{space 1}    1.87{col 49}{space 3}0.061{col 57}{space 4}-.0041196{col 70}{space 3} .1774867
{txt}{space 5}interest92 {c |}{col 17}{res}{space 2} .0446243{col 29}{space 2} .0473056{col 40}{space 1}    0.94{col 49}{space 3}0.346{col 57}{space 4} -.048093{col 70}{space 3} .1373417
{txt}{space 9}info92 {c |}{col 17}{res}{space 2} .0227901{col 29}{space 2} .0507105{col 40}{space 1}    0.45{col 49}{space 3}0.653{col 57}{space 4}-.0766006{col 70}{space 3} .1221808
{txt}{space 10}edu92 {c |}{col 17}{res}{space 2} -.087813{col 29}{space 2} .0514471{col 40}{space 1}   -1.71{col 49}{space 3}0.088{col 57}{space 4}-.1886475{col 70}{space 3} .0130215
{txt}{space 10}age92 {c |}{col 17}{res}{space 2} .0033497{col 29}{space 2} .0462085{col 40}{space 1}    0.07{col 49}{space 3}0.942{col 57}{space 4}-.0872172{col 70}{space 3} .0939167
{txt}{space 7}income92 {c |}{col 17}{res}{space 2} .0687193{col 29}{space 2} .0493725{col 40}{space 1}    1.39{col 49}{space 3}0.164{col 57}{space 4} -.028049{col 70}{space 3} .1654877
{txt}{space 7}female92 {c |}{col 17}{res}{space 2} .0462655{col 29}{space 2} .0449866{col 40}{space 1}    1.03{col 49}{space 3}0.304{col 57}{space 4}-.0419066{col 70}{space 3} .1344376
{txt}{space 8}black92 {c |}{col 17}{res}{space 2}-.0016115{col 29}{space 2} .0455224{col 40}{space 1}   -0.04{col 49}{space 3}0.972{col 57}{space 4}-.0908337{col 70}{space 3} .0876107
{txt}{space 8}south92 {c |}{col 17}{res}{space 2} -.039963{col 29}{space 2} .0447556{col 40}{space 1}   -0.89{col 49}{space 3}0.372{col 57}{space 4}-.1276824{col 70}{space 3} .0477564
{txt}{space 10}_cons {c |}{col 17}{res}{space 2}-.1016299{col 29}{space 2} .2393738{col 40}{space 1}   -0.42{col 49}{space 3}0.671{col 57}{space 4}-.5707938{col 70}{space 3} .3675341
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}var(e.ppol96){c |}{col 17}{res}{space 2} .6780951{col 29}{space 2} .0366418{col 57}{space 4} .6099507{col 70}{space 3} .7538526
{txt}var(e.diffid~96){c |}{col 17}{res}{space 2} .6525706{col 29}{space 2} .0363542{col 57}{space 4} .5850698{col 70}{space 3} .7278591
{txt}var(e.diffca~96){c |}{col 17}{res}{space 2} .7283592{col 29}{space 2} .0366922{col 57}{space 4} .6598801{col 70}{space 3} .8039448
{txt}var(e.partyd~96){c |}{col 17}{res}{space 2}  .687175{col 29}{space 2} .0367039{col 57}{space 4} .6188741{col 70}{space 3} .7630137
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
LR test of model vs. saturated: chi2({res:6})   = {res:   300.97}, Prob > chi2 = {res}0.0000
{txt}
{com}.         
.         
. * Disagregating perceived polarization scales
. sem (pdiffideo96 <- pdiffideo92 affectpol92 pidstrength92 ideostrength92 ///
>         interest92 info92 edu92 age92 income92 female92 ///
>         black92 south92) ///
>         (affectpol96 <- affectpol92 pdiffideo92 pidstrength92 ideostrength92   ///
>         interest92 info92 edu92 age92 income92 female92  ///
>         black92 south92) if rep96 != ., standardized
{res}{txt}(189 observations with missing values excluded)

Endogenous variables

{p 0 11 2}Observed:{space 2}{res}pdiffideo96 affectpol96{p_end}
{txt}
Exogenous variables

{p 0 11 2}Observed:{space 2}{res}pdiffideo92 affectpol92 pidstrength92 ideostrength92 interest92 info92 edu92 age92 income92 female92 black92 south92{p_end}
{txt}
Fitting target model:

Iteration 0:{space 3}log likelihood = {res: -1606.001}  
Iteration 1:{space 3}log likelihood = {res: -1606.001}  

{col 1}Structural equation model{col 49}Number of obs{col 67}= {res}       360
{txt}{col 1}Estimation method{col 20}= {res}ml
{txt}{col 1}Log likelihood{col 20}= {res} -1606.001

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}      OIM
{col 1}   Standardized{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}Structural     {col 17}{txt}{c |}
{space 2}{col 3}pdiffideo96  {col 17}{c |}
{space 4}pdiffideo92 {c |}{col 17}{res}{space 2} .4226333{col 29}{space 2} .0442401{col 40}{space 1}    9.55{col 49}{space 3}0.000{col 57}{space 4} .3359244{col 70}{space 3} .5093423
{txt}{space 4}affectpol92 {c |}{col 17}{res}{space 2} .0017862{col 29}{space 2} .0529988{col 40}{space 1}    0.03{col 49}{space 3}0.973{col 57}{space 4}-.1020895{col 70}{space 3} .1056619
{txt}{space 2}pidstrength92 {c |}{col 17}{res}{space 2} .1137644{col 29}{space 2}  .049027{col 40}{space 1}    2.32{col 49}{space 3}0.020{col 57}{space 4} .0176732{col 70}{space 3} .2098556
{txt}{space 2}ideostreng~92 {c |}{col 17}{res}{space 2}-.0466662{col 29}{space 2} .0498885{col 40}{space 1}   -0.94{col 49}{space 3}0.350{col 57}{space 4}-.1444458{col 70}{space 3} .0511134
{txt}{space 5}interest92 {c |}{col 17}{res}{space 2}-.0682535{col 29}{space 2} .0483862{col 40}{space 1}   -1.41{col 49}{space 3}0.158{col 57}{space 4}-.1630888{col 70}{space 3} .0265817
{txt}{space 9}info92 {c |}{col 17}{res}{space 2} .0936287{col 29}{space 2} .0531794{col 40}{space 1}    1.76{col 49}{space 3}0.078{col 57}{space 4}-.0106011{col 70}{space 3} .1978584
{txt}{space 10}edu92 {c |}{col 17}{res}{space 2}-.0010462{col 29}{space 2} .0545765{col 40}{space 1}   -0.02{col 49}{space 3}0.985{col 57}{space 4}-.1080141{col 70}{space 3} .1059218
{txt}{space 10}age92 {c |}{col 17}{res}{space 2} .0177425{col 29}{space 2} .0484779{col 40}{space 1}    0.37{col 49}{space 3}0.714{col 57}{space 4}-.0772725{col 70}{space 3} .1127575
{txt}{space 7}income92 {c |}{col 17}{res}{space 2} .0212035{col 29}{space 2} .0508319{col 40}{space 1}    0.42{col 49}{space 3}0.677{col 57}{space 4}-.0784251{col 70}{space 3} .1208321
{txt}{space 7}female92 {c |}{col 17}{res}{space 2}-.0336733{col 29}{space 2} .0471695{col 40}{space 1}   -0.71{col 49}{space 3}0.475{col 57}{space 4}-.1261238{col 70}{space 3} .0587771
{txt}{space 8}black92 {c |}{col 17}{res}{space 2}-.1151911{col 29}{space 2} .0466824{col 40}{space 1}   -2.47{col 49}{space 3}0.014{col 57}{space 4}-.2066869{col 70}{space 3}-.0236953
{txt}{space 8}south92 {c |}{col 17}{res}{space 2}  .071597{col 29}{space 2} .0464975{col 40}{space 1}    1.54{col 49}{space 3}0.124{col 57}{space 4}-.0195363{col 70}{space 3} .1627304
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 1.092159{col 29}{space 2}  .254237{col 40}{space 1}    4.30{col 49}{space 3}0.000{col 57}{space 4} .5938641{col 70}{space 3} 1.590455
{space 2}{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}affectpol96  {col 17}{c |}
{space 4}pdiffideo92 {c |}{col 17}{res}{space 2}  .064218{col 29}{space 2} .0455709{col 40}{space 1}    1.41{col 49}{space 3}0.159{col 57}{space 4}-.0250993{col 70}{space 3} .1535353
{txt}{space 4}affectpol92 {c |}{col 17}{res}{space 2} .5231786{col 29}{space 2} .0418632{col 40}{space 1}   12.50{col 49}{space 3}0.000{col 57}{space 4} .4411282{col 70}{space 3} .6052289
{txt}{space 2}pidstrength92 {c |}{col 17}{res}{space 2} .0109299{col 29}{space 2} .0454731{col 40}{space 1}    0.24{col 49}{space 3}0.810{col 57}{space 4}-.0781956{col 70}{space 3} .1000555
{txt}{space 2}ideostreng~92 {c |}{col 17}{res}{space 2}  .088787{col 29}{space 2} .0457869{col 40}{space 1}    1.94{col 49}{space 3}0.052{col 57}{space 4}-.0009537{col 70}{space 3} .1785277
{txt}{space 5}interest92 {c |}{col 17}{res}{space 2} .0430004{col 29}{space 2} .0446217{col 40}{space 1}    0.96{col 49}{space 3}0.335{col 57}{space 4}-.0444566{col 70}{space 3} .1304574
{txt}{space 9}info92 {c |}{col 17}{res}{space 2} .0256874{col 29}{space 2} .0491553{col 40}{space 1}    0.52{col 49}{space 3}0.601{col 57}{space 4}-.0706553{col 70}{space 3}   .12203
{txt}{space 10}edu92 {c |}{col 17}{res}{space 2}-.1086167{col 29}{space 2}  .049973{col 40}{space 1}   -2.17{col 49}{space 3}0.030{col 57}{space 4} -.206562{col 70}{space 3}-.0106714
{txt}{space 10}age92 {c |}{col 17}{res}{space 2}-.0362011{col 29}{space 2} .0446035{col 40}{space 1}   -0.81{col 49}{space 3}0.417{col 57}{space 4}-.1236223{col 70}{space 3} .0512202
{txt}{space 7}income92 {c |}{col 17}{res}{space 2} .0767912{col 29}{space 2} .0466625{col 40}{space 1}    1.65{col 49}{space 3}0.100{col 57}{space 4}-.0146656{col 70}{space 3} .1682481
{txt}{space 7}female92 {c |}{col 17}{res}{space 2}-.0086899{col 29}{space 2} .0434534{col 40}{space 1}   -0.20{col 49}{space 3}0.841{col 57}{space 4} -.093857{col 70}{space 3} .0764772
{txt}{space 8}black92 {c |}{col 17}{res}{space 2}-.0257706{col 29}{space 2}  .043326{col 40}{space 1}   -0.59{col 49}{space 3}0.552{col 57}{space 4}-.1106881{col 70}{space 3} .0591469
{txt}{space 8}south92 {c |}{col 17}{res}{space 2}-.0704458{col 29}{space 2} .0428158{col 40}{space 1}   -1.65{col 49}{space 3}0.100{col 57}{space 4}-.1543633{col 70}{space 3} .0134716
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .5800142{col 29}{space 2} .2269797{col 40}{space 1}    2.56{col 49}{space 3}0.011{col 57}{space 4} .1351422{col 70}{space 3} 1.024886
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
var(e.pdiffid~6){c |}{col 17}{res}{space 2} .7415679{col 29}{space 2} .0370816{col 57}{space 4} .6723373{col 70}{space 3} .8179272
{txt}var(e.affect~96){c |}{col 17}{res}{space 2} .6284808{col 29}{space 2} .0364366{col 57}{space 4} .5609744{col 70}{space 3} .7041108
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
LR test of model vs. saturated: chi2({res:1})   = {res:    28.51}, Prob > chi2 = {res}0.0000
{txt}
{com}.         
. sem (pdiffservice96 <- pdiffservice92 affectpol92 pidstrength92 ideostrength92 ///
>         interest92 info92 edu92 age92 income92 female92 ///
>         black92 south92) ///
>         (affectpol96 <- affectpol92 pdiffservice92 pidstrength92 ideostrength92   ///
>         interest92 info92 edu92 age92 income92 female92  ///
>         black92 south92) if rep96 != ., standardized
{res}{txt}(209 observations with missing values excluded)

Endogenous variables

{p 0 11 2}Observed:{space 2}{res}pdiffservice96 affectpol96{p_end}
{txt}
Exogenous variables

{p 0 11 2}Observed:{space 2}{res}pdiffservice92 affectpol92 pidstrength92 ideostrength92 interest92 info92 edu92 age92 income92 female92 black92 south92{p_end}
{txt}
Fitting target model:

Iteration 0:{space 3}log likelihood = {res: -1540.431}  
Iteration 1:{space 3}log likelihood = {res: -1540.431}  

{col 1}Structural equation model{col 49}Number of obs{col 67}= {res}       340
{txt}{col 1}Estimation method{col 20}= {res}ml
{txt}{col 1}Log likelihood{col 20}= {res} -1540.431

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}      OIM
{col 1}   Standardized{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}Structural     {col 17}{txt}{c |}
{space 2}{col 3}pdiffservi~96{col 17}{c |}
{space 2}pdiffservi~92 {c |}{col 17}{res}{space 2} .1668653{col 29}{space 2} .0533337{col 40}{space 1}    3.13{col 49}{space 3}0.002{col 57}{space 4} .0623331{col 70}{space 3} .2713974
{txt}{space 4}affectpol92 {c |}{col 17}{res}{space 2} .2697135{col 29}{space 2} .0574314{col 40}{space 1}    4.70{col 49}{space 3}0.000{col 57}{space 4} .1571501{col 70}{space 3} .3822769
{txt}{space 2}pidstrength92 {c |}{col 17}{res}{space 2} .0153865{col 29}{space 2} .0550632{col 40}{space 1}    0.28{col 49}{space 3}0.780{col 57}{space 4}-.0925355{col 70}{space 3} .1233085
{txt}{space 2}ideostreng~92 {c |}{col 17}{res}{space 2} .0258814{col 29}{space 2} .0540011{col 40}{space 1}    0.48{col 49}{space 3}0.632{col 57}{space 4}-.0799589{col 70}{space 3} .1317217
{txt}{space 5}interest92 {c |}{col 17}{res}{space 2}-.0696208{col 29}{space 2} .0534533{col 40}{space 1}   -1.30{col 49}{space 3}0.193{col 57}{space 4}-.1743874{col 70}{space 3} .0351457
{txt}{space 9}info92 {c |}{col 17}{res}{space 2} .1370169{col 29}{space 2} .0579153{col 40}{space 1}    2.37{col 49}{space 3}0.018{col 57}{space 4} .0235049{col 70}{space 3} .2505289
{txt}{space 10}edu92 {c |}{col 17}{res}{space 2}-.0563654{col 29}{space 2} .0600988{col 40}{space 1}   -0.94{col 49}{space 3}0.348{col 57}{space 4}-.1741568{col 70}{space 3}  .061426
{txt}{space 10}age92 {c |}{col 17}{res}{space 2}-.0523624{col 29}{space 2} .0521734{col 40}{space 1}   -1.00{col 49}{space 3}0.316{col 57}{space 4}-.1546204{col 70}{space 3} .0498956
{txt}{space 7}income92 {c |}{col 17}{res}{space 2} .0158761{col 29}{space 2} .0562256{col 40}{space 1}    0.28{col 49}{space 3}0.778{col 57}{space 4}-.0943241{col 70}{space 3} .1260763
{txt}{space 7}female92 {c |}{col 17}{res}{space 2}  .033385{col 29}{space 2} .0512308{col 40}{space 1}    0.65{col 49}{space 3}0.515{col 57}{space 4}-.0670255{col 70}{space 3} .1337955
{txt}{space 8}black92 {c |}{col 17}{res}{space 2} .0416147{col 29}{space 2} .0512748{col 40}{space 1}    0.81{col 49}{space 3}0.417{col 57}{space 4}-.0588821{col 70}{space 3} .1421114
{txt}{space 8}south92 {c |}{col 17}{res}{space 2}-.0341626{col 29}{space 2} .0507126{col 40}{space 1}   -0.67{col 49}{space 3}0.501{col 57}{space 4}-.1335575{col 70}{space 3} .0652323
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .9867979{col 29}{space 2} .2618426{col 40}{space 1}    3.77{col 49}{space 3}0.000{col 57}{space 4} .4735959{col 70}{space 3}      1.5
{space 2}{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}affectpol96  {col 17}{c |}
{space 2}pdiffservi~92 {c |}{col 17}{res}{space 2} .1120219{col 29}{space 2} .0471709{col 40}{space 1}    2.37{col 49}{space 3}0.018{col 57}{space 4} .0195687{col 70}{space 3} .2044752
{txt}{space 4}affectpol92 {c |}{col 17}{res}{space 2} .4626188{col 29}{space 2} .0468654{col 40}{space 1}    9.87{col 49}{space 3}0.000{col 57}{space 4} .3707643{col 70}{space 3} .5544733
{txt}{space 2}pidstrength92 {c |}{col 17}{res}{space 2} .0493089{col 29}{space 2} .0481764{col 40}{space 1}    1.02{col 49}{space 3}0.306{col 57}{space 4}-.0451151{col 70}{space 3} .1437329
{txt}{space 2}ideostreng~92 {c |}{col 17}{res}{space 2} .1267514{col 29}{space 2} .0469009{col 40}{space 1}    2.70{col 49}{space 3}0.007{col 57}{space 4} .0348272{col 70}{space 3} .2186755
{txt}{space 5}interest92 {c |}{col 17}{res}{space 2} .0123281{col 29}{space 2} .0469541{col 40}{space 1}    0.26{col 49}{space 3}0.793{col 57}{space 4}-.0797003{col 70}{space 3} .1043565
{txt}{space 9}info92 {c |}{col 17}{res}{space 2}  .020258{col 29}{space 2} .0512063{col 40}{space 1}    0.40{col 49}{space 3}0.692{col 57}{space 4}-.0801046{col 70}{space 3} .1206205
{txt}{space 10}edu92 {c |}{col 17}{res}{space 2}-.0541093{col 29}{space 2}  .052654{col 40}{space 1}   -1.03{col 49}{space 3}0.304{col 57}{space 4}-.1573092{col 70}{space 3} .0490906
{txt}{space 10}age92 {c |}{col 17}{res}{space 2}-.0624293{col 29}{space 2} .0456749{col 40}{space 1}   -1.37{col 49}{space 3}0.172{col 57}{space 4}-.1519505{col 70}{space 3} .0270919
{txt}{space 7}income92 {c |}{col 17}{res}{space 2} .0450861{col 29}{space 2} .0492061{col 40}{space 1}    0.92{col 49}{space 3}0.360{col 57}{space 4}-.0513561{col 70}{space 3} .1415282
{txt}{space 7}female92 {c |}{col 17}{res}{space 2}-.0319177{col 29}{space 2} .0448798{col 40}{space 1}   -0.71{col 49}{space 3}0.477{col 57}{space 4}-.1198805{col 70}{space 3}  .056045
{txt}{space 8}black92 {c |}{col 17}{res}{space 2}-.0367527{col 29}{space 2} .0449274{col 40}{space 1}   -0.82{col 49}{space 3}0.413{col 57}{space 4}-.1248088{col 70}{space 3} .0513034
{txt}{space 8}south92 {c |}{col 17}{res}{space 2}-.0465308{col 29}{space 2} .0443958{col 40}{space 1}   -1.05{col 49}{space 3}0.295{col 57}{space 4} -.133545{col 70}{space 3} .0404833
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .5940907{col 29}{space 2} .2264699{col 40}{space 1}    2.62{col 49}{space 3}0.009{col 57}{space 4} .1502179{col 70}{space 3} 1.037963
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
var(e.pdiffs~96){c |}{col 17}{res}{space 2} .8272538{col 29}{space 2} .0356466{col 57}{space 4} .7602567{col 70}{space 3}  .900155
{txt}var(e.affect~96){c |}{col 17}{res}{space 2} .6347235{col 29}{space 2} .0376178{col 57}{space 4} .5651151{col 70}{space 3} .7129059
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
LR test of model vs. saturated: chi2({res:1})   = {res:    90.66}, Prob > chi2 = {res}0.0000
{txt}
{com}.         
. sem (pdiffjobs96 <- pdiffjobs92 affectpol92 pidstrength92 ideostrength92 ///
>         interest92 info92 edu92 age92 income92 female92 ///
>         black92 south92) ///
>         (affectpol96 <- affectpol92 pdiffjobs92 pidstrength92 ideostrength92   ///
>         interest92 info92 edu92 age92 income92 female92  ///
>         black92 south92) if rep96 != ., standardized
{res}{txt}(211 observations with missing values excluded)

Endogenous variables

{p 0 11 2}Observed:{space 2}{res}pdiffjobs96 affectpol96{p_end}
{txt}
Exogenous variables

{p 0 11 2}Observed:{space 2}{res}pdiffjobs92 affectpol92 pidstrength92 ideostrength92 interest92 info92 edu92 age92 income92 female92 black92 south92{p_end}
{txt}
Fitting target model:

Iteration 0:{space 3}log likelihood = {res:-1603.7532}  
Iteration 1:{space 3}log likelihood = {res:-1603.7532}  

{col 1}Structural equation model{col 49}Number of obs{col 67}= {res}       338
{txt}{col 1}Estimation method{col 20}= {res}ml
{txt}{col 1}Log likelihood{col 20}= {res}-1603.7532

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}      OIM
{col 1}   Standardized{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}Structural     {col 17}{txt}{c |}
{space 2}{col 3}pdiffjobs96  {col 17}{c |}
{space 4}pdiffjobs92 {c |}{col 17}{res}{space 2} .2298711{col 29}{space 2} .0528263{col 40}{space 1}    4.35{col 49}{space 3}0.000{col 57}{space 4} .1263334{col 70}{space 3} .3334088
{txt}{space 4}affectpol92 {c |}{col 17}{res}{space 2} .1717841{col 29}{space 2} .0584275{col 40}{space 1}    2.94{col 49}{space 3}0.003{col 57}{space 4} .0572682{col 70}{space 3} .2862999
{txt}{space 2}pidstrength92 {c |}{col 17}{res}{space 2} .0054491{col 29}{space 2} .0538689{col 40}{space 1}    0.10{col 49}{space 3}0.919{col 57}{space 4} -.100132{col 70}{space 3} .1110302
{txt}{space 2}ideostreng~92 {c |}{col 17}{res}{space 2}  -.00075{col 29}{space 2} .0540472{col 40}{space 1}   -0.01{col 49}{space 3}0.989{col 57}{space 4}-.1066806{col 70}{space 3} .1051806
{txt}{space 5}interest92 {c |}{col 17}{res}{space 2}-.0261017{col 29}{space 2} .0537787{col 40}{space 1}   -0.49{col 49}{space 3}0.627{col 57}{space 4}-.1315061{col 70}{space 3} .0793027
{txt}{space 9}info92 {c |}{col 17}{res}{space 2}  .210199{col 29}{space 2} .0590385{col 40}{space 1}    3.56{col 49}{space 3}0.000{col 57}{space 4} .0944857{col 70}{space 3} .3259124
{txt}{space 10}edu92 {c |}{col 17}{res}{space 2}-.1334414{col 29}{space 2} .0608267{col 40}{space 1}   -2.19{col 49}{space 3}0.028{col 57}{space 4}-.2526596{col 70}{space 3}-.0142232
{txt}{space 10}age92 {c |}{col 17}{res}{space 2}-.0875587{col 29}{space 2} .0524666{col 40}{space 1}   -1.67{col 49}{space 3}0.095{col 57}{space 4}-.1903914{col 70}{space 3} .0152739
{txt}{space 7}income92 {c |}{col 17}{res}{space 2}-.0072004{col 29}{space 2}  .056715{col 40}{space 1}   -0.13{col 49}{space 3}0.899{col 57}{space 4}-.1183597{col 70}{space 3} .1039588
{txt}{space 7}female92 {c |}{col 17}{res}{space 2} .0351564{col 29}{space 2} .0514352{col 40}{space 1}    0.68{col 49}{space 3}0.494{col 57}{space 4}-.0656547{col 70}{space 3} .1359676
{txt}{space 8}black92 {c |}{col 17}{res}{space 2} .0795556{col 29}{space 2} .0505413{col 40}{space 1}    1.57{col 49}{space 3}0.115{col 57}{space 4}-.0195035{col 70}{space 3} .1786148
{txt}{space 8}south92 {c |}{col 17}{res}{space 2} .0469561{col 29}{space 2} .0512679{col 40}{space 1}    0.92{col 49}{space 3}0.360{col 57}{space 4}-.0535273{col 70}{space 3} .1474394
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .8052335{col 29}{space 2} .2634639{col 40}{space 1}    3.06{col 49}{space 3}0.002{col 57}{space 4} .2888538{col 70}{space 3} 1.321613
{space 2}{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}affectpol96  {col 17}{c |}
{space 4}pdiffjobs92 {c |}{col 17}{res}{space 2} .0106797{col 29}{space 2} .0482886{col 40}{space 1}    0.22{col 49}{space 3}0.825{col 57}{space 4}-.0839642{col 70}{space 3} .1053236
{txt}{space 4}affectpol92 {c |}{col 17}{res}{space 2} .5161522{col 29}{space 2} .0455747{col 40}{space 1}   11.33{col 49}{space 3}0.000{col 57}{space 4} .4268274{col 70}{space 3}  .605477
{txt}{space 2}pidstrength92 {c |}{col 17}{res}{space 2} .0166053{col 29}{space 2} .0476936{col 40}{space 1}    0.35{col 49}{space 3}0.728{col 57}{space 4}-.0768723{col 70}{space 3}  .110083
{txt}{space 2}ideostreng~92 {c |}{col 17}{res}{space 2} .0943495{col 29}{space 2}   .04762{col 40}{space 1}    1.98{col 49}{space 3}0.048{col 57}{space 4} .0010161{col 70}{space 3}  .187683
{txt}{space 5}interest92 {c |}{col 17}{res}{space 2} .0578907{col 29}{space 2} .0475499{col 40}{space 1}    1.22{col 49}{space 3}0.223{col 57}{space 4}-.0353053{col 70}{space 3} .1510867
{txt}{space 9}info92 {c |}{col 17}{res}{space 2} .0271679{col 29}{space 2} .0533992{col 40}{space 1}    0.51{col 49}{space 3}0.611{col 57}{space 4}-.0774926{col 70}{space 3} .1318285
{txt}{space 10}edu92 {c |}{col 17}{res}{space 2}-.1105115{col 29}{space 2}  .054022{col 40}{space 1}   -2.05{col 49}{space 3}0.041{col 57}{space 4}-.2163926{col 70}{space 3}-.0046304
{txt}{space 10}age92 {c |}{col 17}{res}{space 2}-.0676089{col 29}{space 2} .0465575{col 40}{space 1}   -1.45{col 49}{space 3}0.146{col 57}{space 4}  -.15886{col 70}{space 3} .0236422
{txt}{space 7}income92 {c |}{col 17}{res}{space 2} .0442669{col 29}{space 2} .0501718{col 40}{space 1}    0.88{col 49}{space 3}0.378{col 57}{space 4} -.054068{col 70}{space 3} .1426018
{txt}{space 7}female92 {c |}{col 17}{res}{space 2} .0043173{col 29}{space 2} .0455815{col 40}{space 1}    0.09{col 49}{space 3}0.925{col 57}{space 4}-.0850209{col 70}{space 3} .0936554
{txt}{space 8}black92 {c |}{col 17}{res}{space 2}-.0522499{col 29}{space 2} .0448682{col 40}{space 1}   -1.16{col 49}{space 3}0.244{col 57}{space 4}-.1401899{col 70}{space 3} .0356902
{txt}{space 8}south92 {c |}{col 17}{res}{space 2}-.0609932{col 29}{space 2} .0453585{col 40}{space 1}   -1.34{col 49}{space 3}0.179{col 57}{space 4}-.1498943{col 70}{space 3} .0279079
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .7429692{col 29}{space 2} .2335142{col 40}{space 1}    3.18{col 49}{space 3}0.001{col 57}{space 4} .2852898{col 70}{space 3} 1.200649
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
var(e.pdiffj~96){c |}{col 17}{res}{space 2} .8301757{col 29}{space 2} .0356019{col 57}{space 4} .7632494{col 70}{space 3} .9029706
{txt}var(e.affect~96){c |}{col 17}{res}{space 2} .6509262{col 29}{space 2} .0380111{col 57}{space 4}  .580531{col 70}{space 3} .7298575
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
LR test of model vs. saturated: chi2({res:1})   = {res:    88.30}, Prob > chi2 = {res}0.0000
{txt}
{com}.         
. sem (pdiffdefense96 <- pdiffdefense92 affectpol92 pidstrength92 ideostrength92 ///
>         interest92 info92 edu92 age92 income92 female92 ///
>         black92 south92) ///
>         (affectpol96 <- affectpol92 pdiffdefense92 pidstrength92 ideostrength92   ///
>         interest92 info92 edu92 age92 income92 female92  ///
>         black92 south92) if rep96 != ., standardized    
{res}{txt}(231 observations with missing values excluded)

Endogenous variables

{p 0 11 2}Observed:{space 2}{res}pdiffdefense96 affectpol96{p_end}
{txt}
Exogenous variables

{p 0 11 2}Observed:{space 2}{res}pdiffdefense92 affectpol92 pidstrength92 ideostrength92 interest92 info92 edu92 age92 income92 female92 black92 south92{p_end}
{txt}
Fitting target model:

Iteration 0:{space 3}log likelihood = {res:-1333.6398}  
Iteration 1:{space 3}log likelihood = {res:-1333.6398}  

{col 1}Structural equation model{col 49}Number of obs{col 67}= {res}       318
{txt}{col 1}Estimation method{col 20}= {res}ml
{txt}{col 1}Log likelihood{col 20}= {res}-1333.6398

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}      OIM
{col 1}   Standardized{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}Structural     {col 17}{txt}{c |}
{space 2}{col 3}pdiffdefen~96{col 17}{c |}
{space 2}pdiffdefen~92 {c |}{col 17}{res}{space 2}  .211065{col 29}{space 2} .0538502{col 40}{space 1}    3.92{col 49}{space 3}0.000{col 57}{space 4} .1055204{col 70}{space 3} .3166095
{txt}{space 4}affectpol92 {c |}{col 17}{res}{space 2} .2659389{col 29}{space 2} .0599301{col 40}{space 1}    4.44{col 49}{space 3}0.000{col 57}{space 4} .1484782{col 70}{space 3} .3833997
{txt}{space 2}pidstrength92 {c |}{col 17}{res}{space 2}-.0133915{col 29}{space 2} .0563779{col 40}{space 1}   -0.24{col 49}{space 3}0.812{col 57}{space 4}-.1238903{col 70}{space 3} .0971072
{txt}{space 2}ideostreng~92 {c |}{col 17}{res}{space 2}-.0351867{col 29}{space 2} .0572207{col 40}{space 1}   -0.61{col 49}{space 3}0.539{col 57}{space 4}-.1473372{col 70}{space 3} .0769637
{txt}{space 5}interest92 {c |}{col 17}{res}{space 2}-.0201493{col 29}{space 2} .0553771{col 40}{space 1}   -0.36{col 49}{space 3}0.716{col 57}{space 4}-.1286865{col 70}{space 3} .0883879
{txt}{space 9}info92 {c |}{col 17}{res}{space 2} .0753535{col 29}{space 2}  .059478{col 40}{space 1}    1.27{col 49}{space 3}0.205{col 57}{space 4}-.0412214{col 70}{space 3} .1919283
{txt}{space 10}edu92 {c |}{col 17}{res}{space 2}-.0932197{col 29}{space 2} .0640875{col 40}{space 1}   -1.45{col 49}{space 3}0.146{col 57}{space 4}-.2188288{col 70}{space 3} .0323895
{txt}{space 10}age92 {c |}{col 17}{res}{space 2}-.0178839{col 29}{space 2} .0553933{col 40}{space 1}   -0.32{col 49}{space 3}0.747{col 57}{space 4}-.1264527{col 70}{space 3}  .090685
{txt}{space 7}income92 {c |}{col 17}{res}{space 2} .0737692{col 29}{space 2} .0589256{col 40}{space 1}    1.25{col 49}{space 3}0.211{col 57}{space 4}-.0417228{col 70}{space 3} .1892613
{txt}{space 7}female92 {c |}{col 17}{res}{space 2}-.0439916{col 29}{space 2} .0535604{col 40}{space 1}   -0.82{col 49}{space 3}0.411{col 57}{space 4}-.1489681{col 70}{space 3}  .060985
{txt}{space 8}black92 {c |}{col 17}{res}{space 2}-.0109543{col 29}{space 2} .0529791{col 40}{space 1}   -0.21{col 49}{space 3}0.836{col 57}{space 4}-.1147915{col 70}{space 3} .0928829
{txt}{space 8}south92 {c |}{col 17}{res}{space 2}-.0123146{col 29}{space 2} .0531231{col 40}{space 1}   -0.23{col 49}{space 3}0.817{col 57}{space 4} -.116434{col 70}{space 3} .0918048
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .7667657{col 29}{space 2} .2834161{col 40}{space 1}    2.71{col 49}{space 3}0.007{col 57}{space 4} .2112804{col 70}{space 3} 1.322251
{space 2}{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}affectpol96  {col 17}{c |}
{space 2}pdiffdefen~92 {c |}{col 17}{res}{space 2}  .065027{col 29}{space 2} .0464001{col 40}{space 1}    1.40{col 49}{space 3}0.161{col 57}{space 4}-.0259156{col 70}{space 3} .1559695
{txt}{space 4}affectpol92 {c |}{col 17}{res}{space 2} .5233406{col 29}{space 2} .0453108{col 40}{space 1}   11.55{col 49}{space 3}0.000{col 57}{space 4}  .434533{col 70}{space 3} .6121481
{txt}{space 2}pidstrength92 {c |}{col 17}{res}{space 2}  .035062{col 29}{space 2} .0473085{col 40}{space 1}    0.74{col 49}{space 3}0.459{col 57}{space 4} -.057661{col 70}{space 3} .1277849
{txt}{space 2}ideostreng~92 {c |}{col 17}{res}{space 2} .1074574{col 29}{space 2} .0477834{col 40}{space 1}    2.25{col 49}{space 3}0.025{col 57}{space 4} .0138037{col 70}{space 3} .2011111
{txt}{space 5}interest92 {c |}{col 17}{res}{space 2} .0350077{col 29}{space 2} .0464744{col 40}{space 1}    0.75{col 49}{space 3}0.451{col 57}{space 4}-.0560804{col 70}{space 3} .1260958
{txt}{space 9}info92 {c |}{col 17}{res}{space 2} .0466828{col 29}{space 2} .0500366{col 40}{space 1}    0.93{col 49}{space 3}0.351{col 57}{space 4}-.0513872{col 70}{space 3} .1447528
{txt}{space 10}edu92 {c |}{col 17}{res}{space 2}-.0893376{col 29}{space 2} .0538431{col 40}{space 1}   -1.66{col 49}{space 3}0.097{col 57}{space 4} -.194868{col 70}{space 3} .0161929
{txt}{space 10}age92 {c |}{col 17}{res}{space 2}-.0543649{col 29}{space 2} .0464401{col 40}{space 1}   -1.17{col 49}{space 3}0.242{col 57}{space 4}-.1453857{col 70}{space 3} .0366559
{txt}{space 7}income92 {c |}{col 17}{res}{space 2} .0950264{col 29}{space 2} .0493986{col 40}{space 1}    1.92{col 49}{space 3}0.054{col 57}{space 4}-.0017931{col 70}{space 3} .1918458
{txt}{space 7}female92 {c |}{col 17}{res}{space 2}-.0509402{col 29}{space 2} .0449567{col 40}{space 1}   -1.13{col 49}{space 3}0.257{col 57}{space 4}-.1390536{col 70}{space 3} .0371733
{txt}{space 8}black92 {c |}{col 17}{res}{space 2}-.0397511{col 29}{space 2} .0444417{col 40}{space 1}   -0.89{col 49}{space 3}0.371{col 57}{space 4}-.1268553{col 70}{space 3} .0473531
{txt}{space 8}south92 {c |}{col 17}{res}{space 2}-.0359118{col 29}{space 2} .0445716{col 40}{space 1}   -0.81{col 49}{space 3}0.420{col 57}{space 4}-.1232706{col 70}{space 3}  .051447
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .4107587{col 29}{space 2} .2365827{col 40}{space 1}    1.74{col 49}{space 3}0.083{col 57}{space 4}-.0529348{col 70}{space 3} .8744522
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
var(e.pdiffd~96){c |}{col 17}{res}{space 2} .8470526{col 29}{space 2} .0357045{col 57}{space 4} .7798859{col 70}{space 3} .9200041
{txt}var(e.affect~96){c |}{col 17}{res}{space 2} .5971162{col 29}{space 2} .0379856{col 57}{space 4} .5271202{col 70}{space 3} .6764069
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
LR test of model vs. saturated: chi2({res:1})   = {res:    32.21}, Prob > chi2 = {res}0.0000
{txt}
{com}.         
. 
. * Multicollinearity     
. reg ppol96 ppol92 diffideotherm92 diffcandtherm92 partydifftherm92 /// 
>         pidstrength92 ideostrength92 issextreme92 ///
>         interest92 info92 edu92 age92 income92 female92 ///
>         black92 south92

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       402
{txt}{hline 13}{c +}{hline 34}   F(15, 386)      = {res}    10.35
{txt}       Model {c |} {res} 4.09010449        15  .272673632   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 10.1685007       386  .026343266   {txt}R-squared       ={res}    0.2869
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.2591
{txt}       Total {c |} {res} 14.2586052       401  .035557619   {txt}Root MSE        =   {res} .16231

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}         ppol96{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}ppol92 {c |}{col 17}{res}{space 2} .3702929{col 29}{space 2} .0508391{col 40}{space 1}    7.28{col 49}{space 3}0.000{col 57}{space 4} .2703367{col 70}{space 3} .4702491
{txt}diffideotherm92 {c |}{col 17}{res}{space 2} .0009412{col 29}{space 2} .0003954{col 40}{space 1}    2.38{col 49}{space 3}0.018{col 57}{space 4} .0001638{col 70}{space 3} .0017186
{txt}diffcandtherm92 {c |}{col 17}{res}{space 2} .0000466{col 29}{space 2} .0004545{col 40}{space 1}    0.10{col 49}{space 3}0.918{col 57}{space 4}-.0008469{col 70}{space 3} .0009401
{txt}partydiffthe~92 {c |}{col 17}{res}{space 2} .0005397{col 29}{space 2} .0004785{col 40}{space 1}    1.13{col 49}{space 3}0.260{col 57}{space 4} -.000401{col 70}{space 3} .0014805
{txt}{space 2}pidstrength92 {c |}{col 17}{res}{space 2} .0223117{col 29}{space 2}  .028814{col 40}{space 1}    0.77{col 49}{space 3}0.439{col 57}{space 4}-.0343403{col 70}{space 3} .0789637
{txt}{space 1}ideostrength92 {c |}{col 17}{res}{space 2}-.0007124{col 29}{space 2}  .029989{col 40}{space 1}   -0.02{col 49}{space 3}0.981{col 57}{space 4}-.0596746{col 70}{space 3} .0582498
{txt}{space 3}issextreme92 {c |}{col 17}{res}{space 2}  .034629{col 29}{space 2} .0139271{col 40}{space 1}    2.49{col 49}{space 3}0.013{col 57}{space 4} .0072466{col 70}{space 3} .0620114
{txt}{space 5}interest92 {c |}{col 17}{res}{space 2} -.056659{col 29}{space 2} .0304326{col 40}{space 1}   -1.86{col 49}{space 3}0.063{col 57}{space 4}-.1164935{col 70}{space 3} .0031756
{txt}{space 9}info92 {c |}{col 17}{res}{space 2} .1317996{col 29}{space 2} .0430693{col 40}{space 1}    3.06{col 49}{space 3}0.002{col 57}{space 4} .0471198{col 70}{space 3} .2164795
{txt}{space 10}edu92 {c |}{col 17}{res}{space 2}-.0391178{col 29}{space 2} .0358093{col 40}{space 1}   -1.09{col 49}{space 3}0.275{col 57}{space 4}-.1095234{col 70}{space 3} .0312878
{txt}{space 10}age92 {c |}{col 17}{res}{space 2}-.0761144{col 29}{space 2} .0375799{col 40}{space 1}   -2.03{col 49}{space 3}0.044{col 57}{space 4}-.1500014{col 70}{space 3}-.0022274
{txt}{space 7}income92 {c |}{col 17}{res}{space 2} .0080129{col 29}{space 2} .0359281{col 40}{space 1}    0.22{col 49}{space 3}0.824{col 57}{space 4}-.0626264{col 70}{space 3} .0786523
{txt}{space 7}female92 {c |}{col 17}{res}{space 2} .0119525{col 29}{space 2} .0169837{col 40}{space 1}    0.70{col 49}{space 3}0.482{col 57}{space 4}-.0214397{col 70}{space 3} .0453447
{txt}{space 8}black92 {c |}{col 17}{res}{space 2} .0104627{col 29}{space 2} .0298068{col 40}{space 1}    0.35{col 49}{space 3}0.726{col 57}{space 4}-.0481413{col 70}{space 3} .0690667
{txt}{space 8}south92 {c |}{col 17}{res}{space 2} .0025674{col 29}{space 2} .0180429{col 40}{space 1}    0.14{col 49}{space 3}0.887{col 57}{space 4}-.0329073{col 70}{space 3} .0380421
{txt}{space 10}_cons {c |}{col 17}{res}{space 2}  .151628{col 29}{space 2} .0440577{col 40}{space 1}    3.44{col 49}{space 3}0.001{col 57}{space 4} .0650049{col 70}{space 3} .2382512
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. vif

{txt}    Variable {c |}       VIF       1/VIF  
{hline 13}{c +}{hline 22}
partydiff~92 {c |} {res}     2.04    0.490320
{txt}diffcandt~92 {c |} {res}     1.94    0.515116
{txt}diffideot~92 {c |} {res}     1.57    0.635595
{txt}{space 7}edu92 {c |} {res}     1.46    0.683091
{txt}{space 6}info92 {c |} {res}     1.42    0.703771
{txt}{space 6}ppol92 {c |} {res}     1.33    0.749152
{txt}{space 4}income92 {c |} {res}     1.31    0.763223
{txt}pidstreng~92 {c |} {res}     1.30    0.769378
{txt}ideostren~92 {c |} {res}     1.30    0.770271
{txt}{space 2}interest92 {c |} {res}     1.23    0.815874
{txt}{space 7}age92 {c |} {res}     1.15    0.871672
{txt}issextreme92 {c |} {res}     1.14    0.875157
{txt}{space 5}black92 {c |} {res}     1.13    0.882614
{txt}{space 4}female92 {c |} {res}     1.10    0.910561
{txt}{space 5}south92 {c |} {res}     1.07    0.931421
{txt}{hline 13}{c +}{hline 22}
    Mean VIF {c |} {res}     1.37
{txt}
{com}. 
. reg diffideotherm96 ppol92 diffideotherm92 diffcandtherm92 partydifftherm92 /// 
>         pidstrength92 ideostrength92 issextreme92 ///
>         interest92 info92 edu92 age92 income92 female92 ///
>         black92 south92

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       373
{txt}{hline 13}{c +}{hline 34}   F(15, 357)      = {res}    12.72
{txt}       Model {c |} {res} 82795.0168        15  5519.66779   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 154932.254       357  433.983905   {txt}R-squared       ={res}    0.3483
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.3209
{txt}       Total {c |} {res} 237727.271       372  639.051803   {txt}Root MSE        =   {res} 20.832

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}diffideotherm96{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}ppol92 {c |}{col 17}{res}{space 2} 3.790425{col 29}{space 2} 6.733588{col 40}{space 1}    0.56{col 49}{space 3}0.574{col 57}{space 4}-9.452059{col 70}{space 3} 17.03291
{txt}diffideotherm92 {c |}{col 17}{res}{space 2} .4149177{col 29}{space 2} .0522957{col 40}{space 1}    7.93{col 49}{space 3}0.000{col 57}{space 4} .3120715{col 70}{space 3}  .517764
{txt}diffcandtherm92 {c |}{col 17}{res}{space 2} .0606944{col 29}{space 2} .0615612{col 40}{space 1}    0.99{col 49}{space 3}0.325{col 57}{space 4}-.0603739{col 70}{space 3} .1817626
{txt}partydiffthe~92 {c |}{col 17}{res}{space 2} .0710501{col 29}{space 2} .0638853{col 40}{space 1}    1.11{col 49}{space 3}0.267{col 57}{space 4}-.0545887{col 70}{space 3} .1966889
{txt}{space 2}pidstrength92 {c |}{col 17}{res}{space 2} 1.257852{col 29}{space 2} 3.881045{col 40}{space 1}    0.32{col 49}{space 3}0.746{col 57}{space 4}-6.374732{col 70}{space 3} 8.890435
{txt}{space 1}ideostrength92 {c |}{col 17}{res}{space 2} 7.125093{col 29}{space 2} 3.990044{col 40}{space 1}    1.79{col 49}{space 3}0.075{col 57}{space 4}-.7218524{col 70}{space 3} 14.97204
{txt}{space 3}issextreme92 {c |}{col 17}{res}{space 2} 1.133833{col 29}{space 2} 1.862813{col 40}{space 1}    0.61{col 49}{space 3}0.543{col 57}{space 4}-2.529633{col 70}{space 3} 4.797298
{txt}{space 5}interest92 {c |}{col 17}{res}{space 2} -4.47477{col 29}{space 2} 4.037233{col 40}{space 1}   -1.11{col 49}{space 3}0.268{col 57}{space 4}-12.41452{col 70}{space 3} 3.464978
{txt}{space 9}info92 {c |}{col 17}{res}{space 2} 2.138786{col 29}{space 2}  5.90714{col 40}{space 1}    0.36{col 49}{space 3}0.718{col 57}{space 4} -9.47838{col 70}{space 3} 13.75595
{txt}{space 10}edu92 {c |}{col 17}{res}{space 2} 8.212521{col 29}{space 2} 4.743007{col 40}{space 1}    1.73{col 49}{space 3}0.084{col 57}{space 4}-1.115224{col 70}{space 3} 17.54027
{txt}{space 10}age92 {c |}{col 17}{res}{space 2}  2.38586{col 29}{space 2} 5.109351{col 40}{space 1}    0.47{col 49}{space 3}0.641{col 57}{space 4}-7.662349{col 70}{space 3} 12.43407
{txt}{space 7}income92 {c |}{col 17}{res}{space 2} 4.363365{col 29}{space 2} 4.786301{col 40}{space 1}    0.91{col 49}{space 3}0.363{col 57}{space 4}-5.049524{col 70}{space 3} 13.77625
{txt}{space 7}female92 {c |}{col 17}{res}{space 2} .5006372{col 29}{space 2} 2.256091{col 40}{space 1}    0.22{col 49}{space 3}0.825{col 57}{space 4}-3.936261{col 70}{space 3} 4.937536
{txt}{space 8}black92 {c |}{col 17}{res}{space 2}-5.930379{col 29}{space 2} 4.084061{col 40}{space 1}   -1.45{col 49}{space 3}0.147{col 57}{space 4}-13.96222{col 70}{space 3} 2.101462
{txt}{space 8}south92 {c |}{col 17}{res}{space 2}-.0526241{col 29}{space 2} 2.396548{col 40}{space 1}   -0.02{col 49}{space 3}0.982{col 57}{space 4} -4.76575{col 70}{space 3} 4.660501
{txt}{space 10}_cons {c |}{col 17}{res}{space 2}-.6583982{col 29}{space 2} 6.027345{col 40}{space 1}   -0.11{col 49}{space 3}0.913{col 57}{space 4}-12.51196{col 70}{space 3} 11.19517
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. vif

{txt}    Variable {c |}       VIF       1/VIF  
{hline 13}{c +}{hline 22}
partydiff~92 {c |} {res}     2.08    0.480589
{txt}diffcandt~92 {c |} {res}     1.97    0.507341
{txt}diffideot~92 {c |} {res}     1.60    0.625779
{txt}{space 7}edu92 {c |} {res}     1.43    0.697727
{txt}{space 6}info92 {c |} {res}     1.38    0.722338
{txt}{space 6}ppol92 {c |} {res}     1.33    0.751357
{txt}pidstreng~92 {c |} {res}     1.32    0.755952
{txt}ideostren~92 {c |} {res}     1.32    0.756971
{txt}{space 4}income92 {c |} {res}     1.31    0.763614
{txt}{space 2}interest92 {c |} {res}     1.20    0.830497
{txt}issextreme92 {c |} {res}     1.16    0.859464
{txt}{space 7}age92 {c |} {res}     1.15    0.867899
{txt}{space 5}black92 {c |} {res}     1.12    0.889393
{txt}{space 4}female92 {c |} {res}     1.09    0.916727
{txt}{space 5}south92 {c |} {res}     1.08    0.924324
{txt}{hline 13}{c +}{hline 22}
    Mean VIF {c |} {res}     1.37
{txt}
{com}. 
. reg diffcandtherm96 ppol92 diffideotherm92 diffcandtherm92 partydifftherm92 /// 
>         pidstrength92 ideostrength92 issextreme92 ///
>         interest92 info92 edu92 age92 income92 female92 ///
>         black92 south92

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       400
{txt}{hline 13}{c +}{hline 34}   F(15, 384)      = {res}     9.43
{txt}       Model {c |} {res} 69432.2715        15   4628.8181   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 188426.606       384  490.694286   {txt}R-squared       ={res}    0.2693
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.2407
{txt}       Total {c |} {res} 257858.877       399  646.262851   {txt}Root MSE        =   {res} 22.152

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}diffcandtherm96{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}ppol92 {c |}{col 17}{res}{space 2} 14.45477{col 29}{space 2} 6.939746{col 40}{space 1}    2.08{col 49}{space 3}0.038{col 57}{space 4} .8101137{col 70}{space 3} 28.09943
{txt}diffideotherm92 {c |}{col 17}{res}{space 2} .1158051{col 29}{space 2} .0543128{col 40}{space 1}    2.13{col 49}{space 3}0.034{col 57}{space 4} .0090175{col 70}{space 3} .2225928
{txt}diffcandtherm92 {c |}{col 17}{res}{space 2} .2367054{col 29}{space 2} .0621578{col 40}{space 1}    3.81{col 49}{space 3}0.000{col 57}{space 4} .1144931{col 70}{space 3} .3589177
{txt}partydiffthe~92 {c |}{col 17}{res}{space 2} .1097823{col 29}{space 2}  .065448{col 40}{space 1}    1.68{col 49}{space 3}0.094{col 57}{space 4}-.0188989{col 70}{space 3} .2384635
{txt}{space 2}pidstrength92 {c |}{col 17}{res}{space 2} .5867846{col 29}{space 2} 3.940381{col 40}{space 1}    0.15{col 49}{space 3}0.882{col 57}{space 4}-7.160638{col 70}{space 3} 8.334207
{txt}{space 1}ideostrength92 {c |}{col 17}{res}{space 2}  6.94309{col 29}{space 2}  4.13072{col 40}{space 1}    1.68{col 49}{space 3}0.094{col 57}{space 4} -1.17857{col 70}{space 3} 15.06475
{txt}{space 3}issextreme92 {c |}{col 17}{res}{space 2} 2.442622{col 29}{space 2} 1.904514{col 40}{space 1}    1.28{col 49}{space 3}0.200{col 57}{space 4}-1.301959{col 70}{space 3} 6.187203
{txt}{space 5}interest92 {c |}{col 17}{res}{space 2} 4.242558{col 29}{space 2} 4.164098{col 40}{space 1}    1.02{col 49}{space 3}0.309{col 57}{space 4}-3.944728{col 70}{space 3} 12.42984
{txt}{space 9}info92 {c |}{col 17}{res}{space 2} 7.190042{col 29}{space 2} 5.894535{col 40}{space 1}    1.22{col 49}{space 3}0.223{col 57}{space 4}-4.399563{col 70}{space 3} 18.77965
{txt}{space 10}edu92 {c |}{col 17}{res}{space 2}-12.50101{col 29}{space 2} 4.917593{col 40}{space 1}   -2.54{col 49}{space 3}0.011{col 57}{space 4}-22.16979{col 70}{space 3} -2.83223
{txt}{space 10}age92 {c |}{col 17}{res}{space 2}-9.224189{col 29}{space 2} 5.136188{col 40}{space 1}   -1.80{col 49}{space 3}0.073{col 57}{space 4}-19.32276{col 70}{space 3} .8743825
{txt}{space 7}income92 {c |}{col 17}{res}{space 2} 7.505201{col 29}{space 2} 4.913145{col 40}{space 1}    1.53{col 49}{space 3}0.127{col 57}{space 4}-2.154832{col 70}{space 3} 17.16523
{txt}{space 7}female92 {c |}{col 17}{res}{space 2} .0786263{col 29}{space 2} 2.326332{col 40}{space 1}    0.03{col 49}{space 3}0.973{col 57}{space 4}-4.495318{col 70}{space 3}  4.65257
{txt}{space 8}black92 {c |}{col 17}{res}{space 2} 1.862309{col 29}{space 2} 4.137421{col 40}{space 1}    0.45{col 49}{space 3}0.653{col 57}{space 4}-6.272526{col 70}{space 3} 9.997145
{txt}{space 8}south92 {c |}{col 17}{res}{space 2}-3.256226{col 29}{space 2} 2.481489{col 40}{space 1}   -1.31{col 49}{space 3}0.190{col 57}{space 4}-8.135233{col 70}{space 3} 1.622781
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 11.25542{col 29}{space 2} 6.025297{col 40}{space 1}    1.87{col 49}{space 3}0.063{col 57}{space 4}-.5912821{col 70}{space 3} 23.10213
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. vif

{txt}    Variable {c |}       VIF       1/VIF  
{hline 13}{c +}{hline 22}
partydiff~92 {c |} {res}     2.05    0.487426
{txt}diffcandt~92 {c |} {res}     1.95    0.513729
{txt}diffideot~92 {c |} {res}     1.58    0.632729
{txt}{space 7}edu92 {c |} {res}     1.46    0.684329
{txt}{space 6}info92 {c |} {res}     1.42    0.704063
{txt}{space 6}ppol92 {c |} {res}     1.34    0.748158
{txt}{space 4}income92 {c |} {res}     1.32    0.759945
{txt}ideostren~92 {c |} {res}     1.31    0.761965
{txt}pidstreng~92 {c |} {res}     1.30    0.771988
{txt}{space 2}interest92 {c |} {res}     1.23    0.812734
{txt}{space 7}age92 {c |} {res}     1.15    0.872167
{txt}issextreme92 {c |} {res}     1.14    0.875066
{txt}{space 5}black92 {c |} {res}     1.11    0.897534
{txt}{space 4}female92 {c |} {res}     1.10    0.908548
{txt}{space 5}south92 {c |} {res}     1.08    0.927264
{txt}{hline 13}{c +}{hline 22}
    Mean VIF {c |} {res}     1.37
{txt}
{com}. 
. reg partydifftherm92 ppol92 diffideotherm92 diffcandtherm92 partydifftherm92 /// 
>         pidstrength92 ideostrength92 issextreme92 ///
>         interest92 info92 edu92 age92 income92 female92 ///
>         black92 south92

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       404
{txt}{hline 13}{c +}{hline 34}   F(15, 388)      = {res}        .
{txt}       Model {c |} {res} 235635.948        15  15709.0632   {txt}Prob > F        ={res}         .
{txt}    Residual {c |} {res}          0       388           0   {txt}R-squared       ={res}    1.0000
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    1.0000
{txt}       Total {c |} {res} 235635.948       403  584.704586   {txt}Root MSE        =   {res}      0

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}partydiffthe~92{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}ppol92 {c |}{col 17}{res}{space 2} 6.90e-15{col 29}{space 2}        .{col 40}{space 1}       .{col 49}{space 3}    .{col 57}{space 4}        .{col 70}{space 3}        .
{txt}diffideotherm92 {c |}{col 17}{res}{space 2}-1.51e-17{col 29}{space 2}        .{col 40}{space 1}       .{col 49}{space 3}    .{col 57}{space 4}        .{col 70}{space 3}        .
{txt}diffcandtherm92 {c |}{col 17}{res}{space 2}-1.48e-16{col 29}{space 2}        .{col 40}{space 1}       .{col 49}{space 3}    .{col 57}{space 4}        .{col 70}{space 3}        .
{txt}partydiffthe~92 {c |}{col 17}{res}{space 2}        1{col 29}{space 2}        .{col 40}{space 1}       .{col 49}{space 3}    .{col 57}{space 4}        .{col 70}{space 3}        .
{txt}{space 2}pidstrength92 {c |}{col 17}{res}{space 2} 5.91e-15{col 29}{space 2}        .{col 40}{space 1}       .{col 49}{space 3}    .{col 57}{space 4}        .{col 70}{space 3}        .
{txt}{space 1}ideostrength92 {c |}{col 17}{res}{space 2}-6.69e-16{col 29}{space 2}        .{col 40}{space 1}       .{col 49}{space 3}    .{col 57}{space 4}        .{col 70}{space 3}        .
{txt}{space 3}issextreme92 {c |}{col 17}{res}{space 2}-1.05e-15{col 29}{space 2}        .{col 40}{space 1}       .{col 49}{space 3}    .{col 57}{space 4}        .{col 70}{space 3}        .
{txt}{space 5}interest92 {c |}{col 17}{res}{space 2} 1.12e-15{col 29}{space 2}        .{col 40}{space 1}       .{col 49}{space 3}    .{col 57}{space 4}        .{col 70}{space 3}        .
{txt}{space 9}info92 {c |}{col 17}{res}{space 2}-1.65e-15{col 29}{space 2}        .{col 40}{space 1}       .{col 49}{space 3}    .{col 57}{space 4}        .{col 70}{space 3}        .
{txt}{space 10}edu92 {c |}{col 17}{res}{space 2} 2.43e-16{col 29}{space 2}        .{col 40}{space 1}       .{col 49}{space 3}    .{col 57}{space 4}        .{col 70}{space 3}        .
{txt}{space 10}age92 {c |}{col 17}{res}{space 2}-7.08e-16{col 29}{space 2}        .{col 40}{space 1}       .{col 49}{space 3}    .{col 57}{space 4}        .{col 70}{space 3}        .
{txt}{space 7}income92 {c |}{col 17}{res}{space 2} 5.85e-16{col 29}{space 2}        .{col 40}{space 1}       .{col 49}{space 3}    .{col 57}{space 4}        .{col 70}{space 3}        .
{txt}{space 7}female92 {c |}{col 17}{res}{space 2} 3.18e-16{col 29}{space 2}        .{col 40}{space 1}       .{col 49}{space 3}    .{col 57}{space 4}        .{col 70}{space 3}        .
{txt}{space 8}black92 {c |}{col 17}{res}{space 2}-7.45e-16{col 29}{space 2}        .{col 40}{space 1}       .{col 49}{space 3}    .{col 57}{space 4}        .{col 70}{space 3}        .
{txt}{space 8}south92 {c |}{col 17}{res}{space 2}-7.91e-16{col 29}{space 2}        .{col 40}{space 1}       .{col 49}{space 3}    .{col 57}{space 4}        .{col 70}{space 3}        .
{txt}{space 10}_cons {c |}{col 17}{res}{space 2}        0{col 29}{txt}  (omitted)
{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. vif

{txt}    Variable {c |}       VIF       1/VIF  
{hline 13}{c +}{hline 22}
partydiff~92 {c |} {res}     2.05    0.488649
{txt}diffcandt~92 {c |} {res}     1.95    0.513342
{txt}diffideot~92 {c |} {res}     1.56    0.640649
{txt}{space 7}edu92 {c |} {res}     1.46    0.683386
{txt}{space 6}info92 {c |} {res}     1.42    0.702953
{txt}{space 6}ppol92 {c |} {res}     1.34    0.747443
{txt}{space 4}income92 {c |} {res}     1.31    0.763221
{txt}pidstreng~92 {c |} {res}     1.31    0.765640
{txt}ideostren~92 {c |} {res}     1.30    0.769327
{txt}{space 2}interest92 {c |} {res}     1.23    0.815960
{txt}{space 7}age92 {c |} {res}     1.14    0.875475
{txt}issextreme92 {c |} {res}     1.14    0.877585
{txt}{space 5}black92 {c |} {res}     1.13    0.886118
{txt}{space 4}female92 {c |} {res}     1.10    0.908734
{txt}{space 5}south92 {c |} {res}     1.08    0.927802
{txt}{hline 13}{c +}{hline 22}
    Mean VIF {c |} {res}     1.37
{txt}
{com}. 
.         
. 
{txt}end of do-file

{com}. clear

. use "/Users/adamenders/Dropbox/Perceived vs. Affective Polarization/Data and Code/08-09 Panel/2008 panel.dta"
{txt}(Written by R.              )

{com}. do "/var/folders/xb/ddtsf7g93xd57f7hhtnm9lyc0000gp/T//SD59652.000000"
{txt}
{com}. ********************************************************************************
. ********************************************************************************
. ********************************************************************************
. ********************************************************************************
. 
. ****
. ** Open ANES 2008-2009 Panel
. ****
. 
. set more off
{txt}
{com}. 
. * use "2008 panel.dta"
. 
. ********************************************************************************
. 
. ****
. ** Data cleaning and recoding
. ****
. 
. ** WAVE 6 
. 
. * McCain
. 
. * amend const for same sex
. gen gaymccain6 = .
{txt}(4,240 missing values generated)

{com}. replace gaymccain6 = 4 if W6PJ1 == 12
{txt}(327 real changes made)

{com}. replace gaymccain6 = 1 if W6PJ2_OP == 10
{txt}(339 real changes made)

{com}. replace gaymccain6 = 2 if W6PJ2_OP == 11
{txt}(203 real changes made)

{com}. replace gaymccain6 = 3 if W6PJ2_OP == 12
{txt}(51 real changes made)

{com}. replace gaymccain6 = 5 if W6PJ2_FA == 12
{txt}(36 real changes made)

{com}. replace gaymccain6 = 6 if W6PJ2_FA == 11
{txt}(195 real changes made)

{com}. replace gaymccain6 = 7 if W6PJ2_FA== 10
{txt}(250 real changes made)

{com}. 
. * tax the rich
. gen taxmccain6 = . 
{txt}(4,240 missing values generated)

{com}. replace taxmccain6 = 4 if W6PJ4 == 12
{txt}(392 real changes made)

{com}. replace taxmccain6 = 1 if W6PJ5_OP == 10
{txt}(392 real changes made)

{com}. replace taxmccain6 = 2 if W6PJ5_OP == 11
{txt}(312 real changes made)

{com}. replace taxmccain6 = 3 if W6PJ5_OP == 12
{txt}(46 real changes made)

{com}. replace taxmccain6 = 5 if W6PJ5_FA == 12
{txt}(50 real changes made)

{com}. replace taxmccain6 = 6 if W6PJ5_FA == 11
{txt}(138 real changes made)

{com}. replace taxmccain6 = 7 if W6PJ5_FA == 10
{txt}(72 real changes made)

{com}. 
. * gov pay for seniors' prescription drugs 
. gen scriptmccain6 = .
{txt}(4,240 missing values generated)

{com}. replace scriptmccain6 = 4 if W6PJ7 == 12
{txt}(419 real changes made)

{com}. replace scriptmccain6 = 1 if W6PJ8_OP == 10
{txt}(319 real changes made)

{com}. replace scriptmccain6 = 2 if W6PJ8_OP == 11
{txt}(330 real changes made)

{com}. replace scriptmccain6= 3 if  W6PJ8_OP == 12
{txt}(97 real changes made)

{com}. replace scriptmccain6 = 5 if W6PJ8_FA == 12
{txt}(39 real changes made)

{com}. replace scriptmccain6 = 6 if W6PJ8_FA == 11
{txt}(112 real changes made)

{com}. replace scriptmccain6 = 7 if W6PJ8_FA == 10
{txt}(86 real changes made)

{com}. 
. * gov pay for medical care
. gen healthmccain6 = .
{txt}(4,240 missing values generated)

{com}. replace healthmccain6 = 4 if W6PJ13 == 12
{txt}(418 real changes made)

{com}. replace healthmccain6 = 1 if W6PJ14_O == 10
{txt}(433 real changes made)

{com}. replace healthmccain6 = 2 if W6PJ14_O == 11
{txt}(359 real changes made)

{com}. replace healthmccain6= 3 if W6PJ14_O == 12
{txt}(61 real changes made)

{com}. replace healthmccain6 = 5 if W6PJ14_F == 12
{txt}(33 real changes made)

{com}. replace healthmccain6 = 6 if W6PJ14_F == 11
{txt}(71 real changes made)

{com}. replace healthmccain6 = 7 if W6PJ14_F == 10
{txt}(29 real changes made)

{com}. 
. * detain terrorists 
. gen terrormccain6 = .
{txt}(4,240 missing values generated)

{com}. replace terrormccain6 = 4 if W6PJ16 == 12
{txt}(370 real changes made)

{com}. replace terrormccain6 = 1 if W6PJ17_O== 10
{txt}(114 real changes made)

{com}. replace terrormccain6 = 2 if W6PJ17_O == 11
{txt}(179 real changes made)

{com}. replace terrormccain6= 3 if  W6PJ17_O == 12
{txt}(48 real changes made)

{com}. replace terrormccain6 = 5 if W6PJ17_F == 12
{txt}(94 real changes made)

{com}. replace terrormccain6 = 6 if W6PJ17_F == 11
{txt}(283 real changes made)

{com}. replace terrormccain6 = 7 if W6PJ17_F == 10
{txt}(314 real changes made)

{com}. 
. * Need FISA warrant to wiretap terrorists? 
. gen fisamccain6 = .
{txt}(4,240 missing values generated)

{com}. replace fisamccain6 = 4 if W6PJ19 == 12
{txt}(416 real changes made)

{com}. replace fisamccain6 = 1 if W6PJ20_O == 10
{txt}(219 real changes made)

{com}. replace fisamccain6 = 2 if W6PJ20_O == 11
{txt}(275 real changes made)

{com}. replace fisamccain6 = 3 if W6PJ20_O == 12
{txt}(56 real changes made)

{com}. replace fisamccain6 = 5 if W6PJ20_F == 12
{txt}(62 real changes made)

{com}. replace fisamccain6 = 6 if W6PJ20_F == 11
{txt}(220 real changes made)

{com}. replace fisamccain6 = 7 if W6PJ20_F == 10
{txt}(152 real changes made)

{com}. 
. * Let immigrants work for 3 years, then send them back 
. gen immigrantsmccain6 = .
{txt}(4,240 missing values generated)

{com}. replace immigrantsmccain6 = 4 if W6PJ22 == 12
{txt}(443 real changes made)

{com}. replace immigrantsmccain6 = 1 if W6PJ23_O == 10
{txt}(165 real changes made)

{com}. replace immigrantsmccain6 = 2 if W6PJ23_O == 11
{txt}(261 real changes made)

{com}. replace immigrantsmccain6 = 3 if W6PJ23_O == 12
{txt}(51 real changes made)

{com}. replace immigrantsmccain6 = 5 if W6PJ23_F == 12
{txt}(80 real changes made)

{com}. replace immigrantsmccain6 = 6 if W6PJ23_F == 11
{txt}(253 real changes made)

{com}. replace immigrantsmccain6 = 7 if W6PJ23_F == 10
{txt}(149 real changes made)

{com}. 
. * allowing immigrants to become citizens
. gen citizenmccain6 = .
{txt}(4,240 missing values generated)

{com}. replace citizenmccain6 = 4 if W6PJ25 == 12
{txt}(450 real changes made)

{com}. replace citizenmccain6 = 1 if W6PJ26_O == 10
{txt}(157 real changes made)

{com}. replace citizenmccain6 = 2 if W6PJ26_O == 11
{txt}(217 real changes made)

{com}. replace citizenmccain6 = 3 if W6PJ26_O == 12
{txt}(61 real changes made)

{com}. replace citizenmccain6 = 5 if W6PJ26_F == 12
{txt}(87 real changes made)

{com}. replace citizenmccain6 = 6 if W6PJ26_F == 11
{txt}(282 real changes made)

{com}. replace citizenmccain6 = 7 if W6PJ26_F == 10
{txt}(148 real changes made)

{com}. 
. ** Obama-mama
. 
. * amend const for same sex
. gen gayobama6 = .
{txt}(4,240 missing values generated)

{com}. replace gayobama6 = 4 if W6PB1 == 12
{txt}(453 real changes made)

{com}. replace gayobama6 = 1 if W6PB2_OP == 10
{txt}(201 real changes made)

{com}. replace gayobama6 = 2 if W6PB2_OP == 11
{txt}(209 real changes made)

{com}. replace gayobama6 = 3 if W6PB2_OP == 12
{txt}(40 real changes made)

{com}. replace gayobama6 = 5 if W6PB2_FA == 12
{txt}(36 real changes made)

{com}. replace gayobama6 = 6 if W6PB2_FA == 11
{txt}(122 real changes made)

{com}. replace gayobama6 = 7 if W6PB2_FA== 10
{txt}(40 real changes made)

{com}. 
. * tax the rich
. gen taxobama6 = . 
{txt}(4,240 missing values generated)

{com}. replace taxobama6 = 4 if W6PB4 == 12
{txt}(206 real changes made)

{com}. replace taxobama6 = 1 if W6PB5_OP == 10
{txt}(20 real changes made)

{com}. replace taxobama6 = 2 if W6PB5_OP == 11
{txt}(47 real changes made)

{com}. replace taxobama6 = 3 if W6PB5_OP == 12
{txt}(19 real changes made)

{com}. replace taxobama6 = 5 if W6PB5_FA == 12
{txt}(58 real changes made)

{com}. replace taxobama6 = 6 if W6PB5_FA == 11
{txt}(297 real changes made)

{com}. replace taxobama6 = 7 if W6PB5_FA == 10
{txt}(455 real changes made)

{com}. 
. * gov pay for seniors' prescription drugs 
. gen scriptobama6 = .
{txt}(4,240 missing values generated)

{com}. replace scriptobama6 = 4 if W6PB7 == 12
{txt}(234 real changes made)

{com}. replace scriptobama6 = 1 if W6PB8_OP == 10
{txt}(252 real changes made)

{com}. replace scriptobama6 = 2 if W6PB8_OP == 11
{txt}(245 real changes made)

{com}. replace scriptobama6= 3 if  W6PB8_OP == 12
{txt}(62 real changes made)

{com}. replace scriptobama6 = 5 if W6PB8_FA == 12
{txt}(26 real changes made)

{com}. replace scriptobama6 = 6 if W6PB8_FA == 11
{txt}(129 real changes made)

{com}. replace scriptobama6 = 7 if W6PB8_FA == 10
{txt}(153 real changes made)

{com}. 
. * gov pay for medical care
. gen healthobama6 = .
{txt}(4,240 missing values generated)

{com}. replace healthobama6 = 4 if W6PB13 == 12
{txt}(376 real changes made)

{com}. replace healthobama6 = 1 if W6PB14_O == 10
{txt}(56 real changes made)

{com}. replace healthobama6 = 2 if W6PB14_O == 11
{txt}(104 real changes made)

{com}. replace healthobama6= 3 if W6PB14_O == 12
{txt}(25 real changes made)

{com}. replace healthobama6 = 5 if W6PB14_F == 12
{txt}(62 real changes made)

{com}. replace healthobama6 = 6 if W6PB14_F == 11
{txt}(233 real changes made)

{com}. replace healthobama6 = 7 if W6PB14_F == 10
{txt}(243 real changes made)

{com}. 
. * detain terrorists 
. gen terrorobama6 = .
{txt}(4,240 missing values generated)

{com}. replace terrorobama6 = 4 if W6PB16 == 12
{txt}(296 real changes made)

{com}. replace terrorobama6 = 1 if W6PB17_O== 10
{txt}(424 real changes made)

{com}. replace terrorobama6 = 2 if W6PB17_O == 11
{txt}(266 real changes made)

{com}. replace terrorobama6= 3 if  W6PB17_O == 12
{txt}(50 real changes made)

{com}. replace terrorobama6 = 5 if W6PB17_F == 12
{txt}(15 real changes made)

{com}. replace terrorobama6 = 6 if W6PB17_F == 11
{txt}(23 real changes made)

{com}. replace terrorobama6 = 7 if W6PB17_F == 10
{txt}(27 real changes made)

{com}. 
. * Need FISA warrant to wiretap terrorists? 
. gen fisaobama6 = .
{txt}(4,240 missing values generated)

{com}. replace fisaobama6 = 4 if W6PB19 == 12
{txt}(292 real changes made)

{com}. replace fisaobama6 = 1 if W6PB20_O == 10
{txt}(48 real changes made)

{com}. replace fisaobama6 = 2 if W6PB20_O == 11
{txt}(82 real changes made)

{com}. replace fisaobama6 = 3 if W6PB20_O == 12
{txt}(22 real changes made)

{com}. replace fisaobama6 = 5 if W6PB20_F == 12
{txt}(50 real changes made)

{com}. replace fisaobama6 = 6 if W6PB20_F == 11
{txt}(246 real changes made)

{com}. replace fisaobama6 = 7 if W6PB20_F == 10
{txt}(362 real changes made)

{com}. 
. * Let immigrants work for 3 years, then send them back 
. gen immigrantsobama6 = .
{txt}(4,240 missing values generated)

{com}. replace immigrantsobama6 = 4 if W6PB22 == 12
{txt}(467 real changes made)

{com}. replace immigrantsobama6 = 1 if W6PB23_O == 10
{txt}(67 real changes made)

{com}. replace immigrantsobama6 = 2 if W6PB23_O == 11
{txt}(131 real changes made)

{com}. replace immigrantsobama6 = 3 if W6PB23_O == 12
{txt}(24 real changes made)

{com}. replace immigrantsobama6 = 5 if W6PB23_F == 12
{txt}(56 real changes made)

{com}. replace immigrantsobama6 = 6 if W6PB23_F == 11
{txt}(224 real changes made)

{com}. replace immigrantsobama6 = 7 if W6PB23_F == 10
{txt}(132 real changes made)

{com}. 
. * allowing immigrants to become citizens
. gen citizenobama6 = .
{txt}(4,240 missing values generated)

{com}. replace citizenobama6 = 4 if W6PB25 == 12
{txt}(320 real changes made)

{com}. replace citizenobama6 = 1 if W6PB26_O == 10
{txt}(23 real changes made)

{com}. replace citizenobama6 = 2 if W6PB26_O == 11
{txt}(52 real changes made)

{com}. replace citizenobama6 = 3 if W6PB26_O == 12
{txt}(17 real changes made)

{com}. replace citizenobama6 = 5 if W6PB26_F == 12
{txt}(68 real changes made)

{com}. replace citizenobama6 = 6 if W6PB26_F == 11
{txt}(353 real changes made)

{com}. replace citizenobama6 = 7 if W6PB26_F == 10
{txt}(267 real changes made)

{com}. 
. 
. 
. ** WAVE 9
. 
. ** McCain
. * amend const for same sex
. gen gaymccain9 = .
{txt}(4,240 missing values generated)

{com}. replace gaymccain9 = 4 if W9PJ1 == 12
{txt}(550 real changes made)

{com}. replace gaymccain9 = 1 if W9PJ2_O == 10
{txt}(547 real changes made)

{com}. replace gaymccain9 = 2 if W9PJ2_O == 11
{txt}(310 real changes made)

{com}. replace gaymccain9 = 3 if W9PJ2_O == 12
{txt}(60 real changes made)

{com}. replace gaymccain9 = 5 if W9PJ2_F == 12
{txt}(92 real changes made)

{com}. replace gaymccain9 = 6 if W9PJ2_F == 11
{txt}(413 real changes made)

{com}. replace gaymccain9 = 7 if W9PJ2_F== 10
{txt}(719 real changes made)

{com}. 
. * tax the rich
. gen taxmccain9 = . 
{txt}(4,240 missing values generated)

{com}. replace taxmccain9 = 4 if W9PJ4 == 12
{txt}(524 real changes made)

{com}. replace taxmccain9 = 1 if W9PJ5_O == 10
{txt}(1,024 real changes made)

{com}. replace taxmccain9 = 2 if W9PJ5_O == 11
{txt}(582 real changes made)

{com}. replace taxmccain9 = 3 if W9PJ5_O == 12
{txt}(88 real changes made)

{com}. replace taxmccain9 = 5 if W9PJ5_F == 12
{txt}(63 real changes made)

{com}. replace taxmccain9 = 6 if W9PJ5_F == 11
{txt}(257 real changes made)

{com}. replace taxmccain9 = 7 if W9PJ5_F == 10
{txt}(151 real changes made)

{com}. 
. * gov pay for seniors' prescription drugs 
. 
. gen scriptmccain9 = .
{txt}(4,240 missing values generated)

{com}. replace scriptmccain9 = 4 if W9PJ7 == 12
{txt}(609 real changes made)

{com}. replace scriptmccain9 = 1 if W9PJ8_O == 10
{txt}(854 real changes made)

{com}. replace scriptmccain9 = 2 if W9PJ8_O == 11
{txt}(589 real changes made)

{com}. replace scriptmccain9= 3 if  W9PJ8_O == 12
{txt}(99 real changes made)

{com}. replace scriptmccain9 = 5 if W9PJ8_F == 12
{txt}(71 real changes made)

{com}. replace scriptmccain9 = 6 if W9PJ8_F == 11
{txt}(244 real changes made)

{com}. replace scriptmccain9 = 7 if W9PJ8_F == 10
{txt}(221 real changes made)

{com}. 
.  
. * gov pay for medical care
. gen healthmccain9 = .
{txt}(4,240 missing values generated)

{com}. replace healthmccain9 = 4 if W9PJ13 == 12
{txt}(773 real changes made)

{com}. replace healthmccain9 = 1 if W9PJ14_O == 10
{txt}(917 real changes made)

{com}. replace healthmccain9 = 2 if W9PJ14_O == 11
{txt}(639 real changes made)

{com}. replace healthmccain9= 3 if W9PJ14_O == 12
{txt}(98 real changes made)

{com}. replace healthmccain9 = 5 if W9PJ14_F == 12
{txt}(46 real changes made)

{com}. replace healthmccain9 = 6 if W9PJ14_F == 11
{txt}(134 real changes made)

{com}. replace healthmccain9 = 7 if W9PJ14_F == 10
{txt}(82 real changes made)

{com}. 
. * detain terrorists 
. gen terrormccain9 = .
{txt}(4,240 missing values generated)

{com}. replace terrormccain9 = 4 if W9PJ16 == 12
{txt}(664 real changes made)

{com}. replace terrormccain9 = 1 if W9PJ17_O== 10
{txt}(269 real changes made)

{com}. replace terrormccain9 = 2 if W9PJ17_O == 11
{txt}(334 real changes made)

{com}. replace terrormccain9= 3 if  W9PJ17_O == 12
{txt}(64 real changes made)

{com}. replace terrormccain9 = 5 if W9PJ17_F == 12
{txt}(140 real changes made)

{com}. replace terrormccain9 = 6 if W9PJ17_F == 11
{txt}(556 real changes made)

{com}. replace terrormccain9 = 7 if W9PJ17_F == 10
{txt}(659 real changes made)

{com}. 
. * Need FISA warrant to wiretap terrorists? 
. gen fisamccain9 = .
{txt}(4,240 missing values generated)

{com}. replace fisamccain9 = 4 if W9PJ19 == 12
{txt}(694 real changes made)

{com}. replace fisamccain9 = 1 if W9PJ20_O == 10
{txt}(524 real changes made)

{com}. replace fisamccain9 = 2 if W9PJ20_O == 11
{txt}(540 real changes made)

{com}. replace fisamccain9 = 3 if W9PJ20_O == 12
{txt}(96 real changes made)

{com}. replace fisamccain9 = 5 if W9PJ20_F == 12
{txt}(99 real changes made)

{com}. replace fisamccain9 = 6 if W9PJ20_F == 11
{txt}(429 real changes made)

{com}. replace fisamccain9 = 7 if W9PJ20_F == 10
{txt}(304 real changes made)

{com}. 
. * Let immigrants work for 3 years, then send them back 
. gen immigrantsmccain9 = .
{txt}(4,240 missing values generated)

{com}. replace immigrantsmccain9 = 4 if W9PJ22 == 12
{txt}(780 real changes made)

{com}. replace immigrantsmccain9 = 1 if W9PJ23_O == 10
{txt}(396 real changes made)

{com}. replace immigrantsmccain9 = 2 if W9PJ23_O == 11
{txt}(447 real changes made)

{com}. replace immigrantsmccain9 = 3 if W9PJ23_O == 12
{txt}(100 real changes made)

{com}. replace immigrantsmccain9 = 5 if W9PJ23_F == 12
{txt}(119 real changes made)

{com}. replace immigrantsmccain9 = 6 if W9PJ23_F == 11
{txt}(534 real changes made)

{com}. replace immigrantsmccain9 = 7 if W9PJ23_F == 10
{txt}(310 real changes made)

{com}. 
. * allowing immigrants to become citizens
. gen citizenmccain9 = .
{txt}(4,240 missing values generated)

{com}. replace citizenmccain9 = 4 if W9PJ25 == 12
{txt}(855 real changes made)

{com}. replace citizenmccain9 = 1 if W9PJ26_O == 10
{txt}(318 real changes made)

{com}. replace citizenmccain9 = 2 if W9PJ26_O == 11
{txt}(410 real changes made)

{com}. replace citizenmccain9 = 3 if W9PJ26_O == 12
{txt}(93 real changes made)

{com}. replace citizenmccain9 = 5 if W9PJ26_F == 12
{txt}(159 real changes made)

{com}. replace citizenmccain9 = 6 if W9PJ26_F == 11
{txt}(564 real changes made)

{com}. replace citizenmccain9 = 7 if W9PJ26_F == 10
{txt}(286 real changes made)

{com}. 
. 
. 
. ** Obama
. 
. 
. * amend const for same sex
. gen gayobama9 = .
{txt}(4,240 missing values generated)

{com}. replace gayobama9 = 4 if W9PB1 == 12
{txt}(969 real changes made)

{com}. replace gayobama9 = 1 if W9PB2_OP == 10
{txt}(553 real changes made)

{com}. replace gayobama9 = 2 if W9PB2_OP == 11
{txt}(602 real changes made)

{com}. replace gayobama9 = 3 if W9PB2_OP == 12
{txt}(98 real changes made)

{com}. replace gayobama9 = 5 if W9PB2_FA == 12
{txt}(70 real changes made)

{com}. replace gayobama9 = 6 if W9PB2_FA == 11
{txt}(271 real changes made)

{com}. replace gayobama9 = 7 if W9PB2_FA== 10
{txt}(132 real changes made)

{com}. 
. * tax the rich
. gen taxobama9 = . 
{txt}(4,240 missing values generated)

{com}. replace taxobama9 = 4 if W9PB4 == 12
{txt}(304 real changes made)

{com}. replace taxobama9 = 1 if W9PB5_OP == 10
{txt}(60 real changes made)

{com}. replace taxobama9 = 2 if W9PB5_OP == 11
{txt}(108 real changes made)

{com}. replace taxobama9 = 3 if W9PB5_OP == 12
{txt}(19 real changes made)

{com}. replace taxobama9 = 5 if W9PB5_FA == 12
{txt}(99 real changes made)

{com}. replace taxobama9 = 6 if W9PB5_FA == 11
{txt}(710 real changes made)

{com}. replace taxobama9 = 7 if W9PB5_FA == 10
{txt}(1,394 real changes made)

{com}. 
. * gov pay for seniors' prescription drugs 
. gen scriptobama9 = .
{txt}(4,240 missing values generated)

{com}. replace scriptobama9 = 4 if W9PB7 == 12
{txt}(398 real changes made)

{com}. replace scriptobama9 = 1 if W9PB8_OP == 10
{txt}(820 real changes made)

{com}. replace scriptobama9 = 2 if W9PB8_OP == 11
{txt}(574 real changes made)

{com}. replace scriptobama9= 3 if  W9PB8_OP == 12
{txt}(111 real changes made)

{com}. replace scriptobama9 = 5 if W9PB8_FA == 12
{txt}(75 real changes made)

{com}. replace scriptobama9 = 6 if W9PB8_FA == 11
{txt}(334 real changes made)

{com}. replace scriptobama9 = 7 if W9PB8_FA == 10
{txt}(384 real changes made)

{com}. 
. * gov pay for medical care
. gen healthobama9 = .
{txt}(4,240 missing values generated)

{com}. replace healthobama9 = 4 if W9PB13 == 12
{txt}(840 real changes made)

{com}. replace healthobama9 = 1 if W9PB14_O == 10
{txt}(125 real changes made)

{com}. replace healthobama9 = 2 if W9PB14_O == 11
{txt}(245 real changes made)

{com}. replace healthobama9= 3 if W9PB14_O == 12
{txt}(53 real changes made)

{com}. replace healthobama9 = 5 if W9PB14_F == 12
{txt}(133 real changes made)

{com}. replace healthobama9 = 6 if W9PB14_F == 11
{txt}(586 real changes made)

{com}. replace healthobama9 = 7 if W9PB14_F == 10
{txt}(714 real changes made)

{com}. 
. * detain terrorists 
. gen terrorobama9 = .
{txt}(4,240 missing values generated)

{com}. replace terrorobama9 = 4 if W9PB16 == 12
{txt}(637 real changes made)

{com}. replace terrorobama9 = 1 if W9PB17_O== 10
{txt}(1,146 real changes made)

{com}. replace terrorobama9 = 2 if W9PB17_O == 11
{txt}(659 real changes made)

{com}. replace terrorobama9= 3 if  W9PB17_O == 12
{txt}(79 real changes made)

{com}. replace terrorobama9 = 5 if W9PB17_F == 12
{txt}(27 real changes made)

{com}. replace terrorobama9 = 6 if W9PB17_F == 11
{txt}(92 real changes made)

{com}. replace terrorobama9 = 7 if W9PB17_F == 10
{txt}(52 real changes made)

{com}. 
. * Need FISA warrant to wiretap terrorists? 
. gen fisaobama9 = .
{txt}(4,240 missing values generated)

{com}. replace fisaobama9 = 4 if W9PB19 == 12
{txt}(697 real changes made)

{com}. replace fisaobama9 = 1 if W9PB20_O == 10
{txt}(113 real changes made)

{com}. replace fisaobama9 = 2 if W9PB20_O == 11
{txt}(164 real changes made)

{com}. replace fisaobama9 = 3 if W9PB20_O == 12
{txt}(37 real changes made)

{com}. replace fisaobama9 = 5 if W9PB20_F == 12
{txt}(95 real changes made)

{com}. replace fisaobama9 = 6 if W9PB20_F == 11
{txt}(648 real changes made)

{com}. replace fisaobama9 = 7 if W9PB20_F == 10
{txt}(936 real changes made)

{com}. 
. * Let immigrants work for 3 years, then send them back 
. gen immigrantsobama9 = .
{txt}(4,240 missing values generated)

{com}. replace immigrantsobama9 = 4 if W9PB22 == 12
{txt}(1,086 real changes made)

{com}. replace immigrantsobama9 = 1 if W9PB23_O == 10
{txt}(170 real changes made)

{com}. replace immigrantsobama9 = 2 if W9PB23_O == 11
{txt}(314 real changes made)

{com}. replace immigrantsobama9 = 3 if W9PB23_O == 12
{txt}(59 real changes made)

{com}. replace immigrantsobama9 = 5 if W9PB23_F == 12
{txt}(125 real changes made)

{com}. replace immigrantsobama9 = 6 if W9PB23_F == 11
{txt}(609 real changes made)

{com}. replace immigrantsobama9 = 7 if W9PB23_F == 10
{txt}(320 real changes made)

{com}. 
. * allowing immigrants to become citizens
. gen citizenobama9 = .
{txt}(4,240 missing values generated)

{com}. replace citizenobama9 = 4 if W9PB25 == 12
{txt}(732 real changes made)

{com}. replace citizenobama9 = 1 if W9PB26_O == 10
{txt}(61 real changes made)

{com}. replace citizenobama9 = 2 if W9PB26_O == 11
{txt}(129 real changes made)

{com}. replace citizenobama9 = 3 if W9PB26_O == 12
{txt}(32 real changes made)

{com}. replace citizenobama9 = 5 if W9PB26_F == 12
{txt}(148 real changes made)

{com}. replace citizenobama9 = 6 if W9PB26_F == 11
{txt}(897 real changes made)

{com}. replace citizenobama9 = 7 if W9PB26_F == 10
{txt}(690 real changes made)

{com}. 
. 
. * ideological differences
. 
. gen mccainideo6 = .
{txt}(4,240 missing values generated)

{com}. replace mccainideo6 = 1 if W6H10 == 10
{txt}(39 real changes made)

{com}. replace mccainideo6 = 2 if W6H10 == 11
{txt}(78 real changes made)

{com}. replace mccainideo6 = 3 if W6H12 == 10
{txt}(37 real changes made)

{com}. replace mccainideo6 = 4 if W6H12 == 12
{txt}(226 real changes made)

{com}. replace mccainideo6 = 5 if W6H12 == 11
{txt}(172 real changes made)

{com}. replace mccainideo6 = 6 if W6H11 == 11
{txt}(537 real changes made)

{com}. replace mccainideo6 = 7 if W6H11 == 10
{txt}(314 real changes made)

{com}. 
. gen mccainideo9 = .
{txt}(4,240 missing values generated)

{com}. replace mccainideo9 = 1 if W9M10 == 10
{txt}(60 real changes made)

{com}. replace mccainideo9 = 2 if W9M10 == 11
{txt}(139 real changes made)

{com}. replace mccainideo9 = 3 if W9M12 == 10
{txt}(62 real changes made)

{com}. replace mccainideo9 = 4 if W9M12 == 12
{txt}(422 real changes made)

{com}. replace mccainideo9 = 5 if W9M12 == 11
{txt}(378 real changes made)

{com}. replace mccainideo9 = 6 if W9M11 == 11
{txt}(962 real changes made)

{com}. replace mccainideo9 = 7 if W9M11 == 10
{txt}(698 real changes made)

{com}. 
. gen obamaideo6 = .
{txt}(4,240 missing values generated)

{com}. replace obamaideo6 = 1 if W6H6 == 10
{txt}(552 real changes made)

{com}. replace obamaideo6 = 2 if W6H6 == 11
{txt}(382 real changes made)

{com}. replace obamaideo6 = 3 if W6H8 == 10
{txt}(126 real changes made)

{com}. replace obamaideo6 = 4 if W6H8 == 12
{txt}(228 real changes made)

{com}. replace obamaideo6 = 5 if W6H8 == 11
{txt}(27 real changes made)

{com}. replace obamaideo6 = 6 if W6H7 == 11
{txt}(70 real changes made)

{com}. replace obamaideo6 = 7 if W6H7 == 10
{txt}(21 real changes made)

{com}. 
. gen obamaideo9 = .
{txt}(4,240 missing values generated)

{com}. replace obamaideo9 = 1 if W9M6 == 10
{txt}(1,072 real changes made)

{com}. replace obamaideo9 = 2 if W9M6 == 11
{txt}(669 real changes made)

{com}. replace obamaideo9 = 3 if W9M8 == 10
{txt}(336 real changes made)

{com}. replace obamaideo9 = 4 if W9M8 == 12
{txt}(448 real changes made)

{com}. replace obamaideo9 = 5 if W9M8 == 11
{txt}(55 real changes made)

{com}. replace obamaideo9 = 6 if W9M7 == 11
{txt}(107 real changes made)

{com}. replace obamaideo9 = 7 if W9M7 == 10
{txt}(37 real changes made)

{com}. 
. **** perceived candidate differences 
. 
. * wave 6
. 
. gen gay6 = abs(gaymccain6-gayobama6)
{txt}(3,145 missing values generated)

{com}. gen tax6 = abs(taxmccain6-taxobama6)
{txt}(3,142 missing values generated)

{com}. gen script6 = abs(scriptmccain6-scriptobama6)
{txt}(3,143 missing values generated)

{com}. gen health6 = abs(healthmccain6-healthobama6)
{txt}(3,143 missing values generated)

{com}. gen terror6 = abs(terrormccain6-terrorobama6)
{txt}(3,143 missing values generated)

{com}. gen fisa6 = abs(fisamccain6-fisaobama6)
{txt}(3,144 missing values generated)

{com}. gen immigrants6 = abs(immigrantsmccain6-immigrantsobama6)
{txt}(3,145 missing values generated)

{com}. gen citizen6 = abs(citizenmccain6-citizenobama6)
{txt}(3,143 missing values generated)

{com}. gen ideo6 = abs(mccainideo6-obamaideo6)
{txt}(2,844 missing values generated)

{com}. 
. factor gay6-ideo6, ipf
{txt}(obs=1,072)

Factor analysis/correlation{col 50}Number of obs    = {res}     1,072
{col 5}{txt}Method: iterated principal factors{col 50}Retained factors =   {res}       8
{col 5}{txt}Rotation: (unrotated){col 50}Number of params =   {res}      36

{txt}{col 5}{hline 13}{c TT}{hline 60}
{col 5}     Factor  {c |} {ralign 12:Eigenvalue}   Difference        Proportion   Cumulative
{col 5}{hline 13}{c +}{hline 60}
{col 5}{ralign 11:Factor1}  {c |}{res}      2.44655      2.04090            0.6800       0.6800
{txt}{col 5}{ralign 11:Factor2}  {c |}{res}      0.40565      0.11107            0.1128       0.7928
{txt}{col 5}{ralign 11:Factor3}  {c |}{res}      0.29458      0.06550            0.0819       0.8747
{txt}{col 5}{ralign 11:Factor4}  {c |}{res}      0.22909      0.13413            0.0637       0.9383
{txt}{col 5}{ralign 11:Factor5}  {c |}{res}      0.09496      0.01803            0.0264       0.9647
{txt}{col 5}{ralign 11:Factor6}  {c |}{res}      0.07693      0.02740            0.0214       0.9861
{txt}{col 5}{ralign 11:Factor7}  {c |}{res}      0.04953      0.04889            0.0138       0.9999
{txt}{col 5}{ralign 11:Factor8}  {c |}{res}      0.00063      0.00087            0.0002       1.0001
{txt}{col 5}{ralign 11:Factor9}  {c |}{res}     -0.00024            .           -0.0001       1.0000
{txt}{col 5}{hline 13}{c BT}{hline 60}
{col 5}LR test: independent vs. saturated:  chi2({res}36{txt}) ={res} 1495.09{txt} Prob>chi2 ={res} 0.0000

{txt}Factor loadings (pattern matrix) and unique variances

{space 4}{hline 13}{c  TT}{hline 10}{hline 10}{hline 10}{hline 10}{hline 10}{hline 10}
{space 4}{space 0}{ralign 12:Variable}{space 1}{c |}{space 1}{ralign 8:Factor1}{space 1}{space 1}{ralign 8:Factor2}{space 1}{space 1}{ralign 8:Factor3}{space 1}{space 1}{ralign 8:Factor4}{space 1}{space 1}{ralign 8:Factor5}{space 1}{space 1}{ralign 8:Factor6}{space 1}
{space 4}{hline 13}{c   +}{hline 10}{hline 10}{hline 10}{hline 10}{hline 10}{hline 10}
{space 4}{space 0}{ralign 12:gay6}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.4908}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.1246}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.2013}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0100}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0546}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.1656}}}{space 1}
{space 4}{space 0}{ralign 12:tax6}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.6167}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.2539}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0773}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0836}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.1339}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0504}}}{space 1}
{space 4}{space 0}{ralign 12:script6}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.3766}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.2394}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.1550}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.1754}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0199}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0696}}}{space 1}
{space 4}{space 0}{ralign 12:health6}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.5386}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.1928}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0191}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0746}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.1599}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0598}}}{space 1}
{space 4}{space 0}{ralign 12:terror6}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.5915}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0327}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0835}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.2764}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0766}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.1267}}}{space 1}
{space 4}{space 0}{ralign 12:fisa6}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.6227}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.1603}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.2177}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.1916}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0958}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0990}}}{space 1}
{space 4}{space 0}{ralign 12:immigrants6}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.5019}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.3080}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0864}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.1894}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.1012}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0837}}}{space 1}
{space 4}{space 0}{ralign 12:citizen6}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.4880}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.3267}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0094}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.1598}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.1450}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0499}}}{space 1}
{space 4}{space 0}{ralign 12:ideo6}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.4071}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0528}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.4022}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.1058}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0423}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0564}}}{space 1}
{space 4}{hline 13}{c  BT}{hline 10}{hline 10}{hline 10}{hline 10}{hline 10}{hline 10}

{space 4}{hline 13}{c  TT}{hline 10}{hline 10}{c  TT}{hline 14}
{space 4}{space 0}{ralign 12:Variable}{space 1}{c |}{space 1}{ralign 8:Factor7}{space 1}{space 1}{ralign 8:Factor8}{space 1}{c |}{space 1}{ralign 12:Uniqueness}{space 1}
{space 4}{hline 13}{c   +}{hline 10}{hline 10}{c   +}{hline 14}
{space 4}{space 0}{ralign 12:gay6}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.0978}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0062}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.6630}}}{space 1}
{space 4}{space 0}{ralign 12:tax6}{space 1}{c |}{space 1}{ralign 8:{res:{sf: -0.0872}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0099}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.5141}}}{space 1}
{space 4}{space 0}{ralign 12:script6}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.1318}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0019}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.7235}}}{space 1}
{space 4}{space 0}{ralign 12:health6}{space 1}{c |}{space 1}{ralign 8:{res:{sf: -0.1053}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0118}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.6265}}}{space 1}
{space 4}{space 0}{ralign 12:terror6}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.0456}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0067}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.5416}}}{space 1}
{space 4}{space 0}{ralign 12:fisa6}{space 1}{c |}{space 1}{ralign 8:{res:{sf: -0.0107}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0080}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.4832}}}{space 1}
{space 4}{space 0}{ralign 12:immigrants6}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.0260}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0093}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.5919}}}{space 1}
{space 4}{space 0}{ralign 12:citizen6}{space 1}{c |}{space 1}{ralign 8:{res:{sf: -0.0234}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0112}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.6053}}}{space 1}
{space 4}{space 0}{ralign 12:ideo6}{space 1}{c |}{space 1}{ralign 8:{res:{sf: -0.0224}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0059}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.6530}}}{space 1}
{space 4}{hline 13}{c  BT}{hline 10}{hline 10}{c  BT}{hline 14}

{com}. alpha gay6-ideo6, gen(canddiff6)

{txt}Test scale = mean(unstandardized items)

Average interitem covariance:{col 34}{res} .9631484
{txt}Number of items in the scale:{col 34}{res}        9
{txt}Scale reliability coefficient:{col 34}{res}   0.7534
{txt}
{com}. 
. * wave 9
. 
. gen gay9 = abs(gaymccain9-gayobama9)
{txt}(1,553 missing values generated)

{com}. gen tax9 = abs(taxmccain9-taxobama9)
{txt}(1,552 missing values generated)

{com}. gen script9 = abs(scriptmccain9-scriptobama9)
{txt}(1,553 missing values generated)

{com}. gen health9 = abs(healthmccain9-healthobama9)
{txt}(1,552 missing values generated)

{com}. gen terror9 = abs(terrormccain9-terrorobama9)
{txt}(1,555 missing values generated)

{com}. gen fisa9 = abs(fisamccain9-fisaobama9)
{txt}(1,558 missing values generated)

{com}. gen immigrants9 = abs(immigrantsmccain9-immigrantsobama9)
{txt}(1,562 missing values generated)

{com}. gen citizen9 = abs(citizenmccain9-citizenobama9)
{txt}(1,557 missing values generated)

{com}. gen ideo9 = abs(mccainideo9-obamaideo9)
{txt}(1,519 missing values generated)

{com}. 
. factor gay9-ideo9, ipf
{txt}(obs=2,659)

Factor analysis/correlation{col 50}Number of obs    = {res}     2,659
{col 5}{txt}Method: iterated principal factors{col 50}Retained factors =   {res}       8
{col 5}{txt}Rotation: (unrotated){col 50}Number of params =   {res}      36

{txt}{col 5}{hline 13}{c TT}{hline 60}
{col 5}     Factor  {c |} {ralign 12:Eigenvalue}   Difference        Proportion   Cumulative
{col 5}{hline 13}{c +}{hline 60}
{col 5}{ralign 11:Factor1}  {c |}{res}      2.09676      1.60297            0.6394       0.6394
{txt}{col 5}{ralign 11:Factor2}  {c |}{res}      0.49379      0.20181            0.1506       0.7900
{txt}{col 5}{ralign 11:Factor3}  {c |}{res}      0.29198      0.05693            0.0890       0.8791
{txt}{col 5}{ralign 11:Factor4}  {c |}{res}      0.23505      0.13977            0.0717       0.9508
{txt}{col 5}{ralign 11:Factor5}  {c |}{res}      0.09529      0.05251            0.0291       0.9798
{txt}{col 5}{ralign 11:Factor6}  {c |}{res}      0.04278      0.02489            0.0130       0.9929
{txt}{col 5}{ralign 11:Factor7}  {c |}{res}      0.01788      0.01212            0.0055       0.9983
{txt}{col 5}{ralign 11:Factor8}  {c |}{res}      0.00576      0.00601            0.0018       1.0001
{txt}{col 5}{ralign 11:Factor9}  {c |}{res}     -0.00024            .           -0.0001       1.0000
{txt}{col 5}{hline 13}{c BT}{hline 60}
{col 5}LR test: independent vs. saturated:  chi2({res}36{txt}) ={res} 2949.78{txt} Prob>chi2 ={res} 0.0000

{txt}Factor loadings (pattern matrix) and unique variances

{space 4}{hline 13}{c  TT}{hline 10}{hline 10}{hline 10}{hline 10}{hline 10}{hline 10}
{space 4}{space 0}{ralign 12:Variable}{space 1}{c |}{space 1}{ralign 8:Factor1}{space 1}{space 1}{ralign 8:Factor2}{space 1}{space 1}{ralign 8:Factor3}{space 1}{space 1}{ralign 8:Factor4}{space 1}{space 1}{ralign 8:Factor5}{space 1}{space 1}{ralign 8:Factor6}{space 1}
{space 4}{hline 13}{c   +}{hline 10}{hline 10}{hline 10}{hline 10}{hline 10}{hline 10}
{space 4}{space 0}{ralign 12:gay9}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.4440}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0374}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0287}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.3134}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0013}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.1109}}}{space 1}
{space 4}{space 0}{ralign 12:tax9}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.5321}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.3214}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0298}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.1628}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.1559}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0509}}}{space 1}
{space 4}{space 0}{ralign 12:script9}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.3238}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0953}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.1698}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0896}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0218}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0680}}}{space 1}
{space 4}{space 0}{ralign 12:health9}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.5244}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.2495}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.1410}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.1319}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.1526}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0386}}}{space 1}
{space 4}{space 0}{ralign 12:terror9}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.5483}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0544}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.3299}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0074}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0371}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0175}}}{space 1}
{space 4}{space 0}{ralign 12:fisa9}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.5742}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0052}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.2756}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0029}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0827}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0304}}}{space 1}
{space 4}{space 0}{ralign 12:immigrants9}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.4498}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.3708}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.1169}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0842}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.1566}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0531}}}{space 1}
{space 4}{space 0}{ralign 12:citizen9}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.4887}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.4073}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.1290}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0518}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.1138}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0710}}}{space 1}
{space 4}{space 0}{ralign 12:ideo9}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.4063}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.1068}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.1626}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.2740}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0390}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.1126}}}{space 1}
{space 4}{hline 13}{c  BT}{hline 10}{hline 10}{hline 10}{hline 10}{hline 10}{hline 10}

{space 4}{hline 13}{c  TT}{hline 10}{hline 10}{c  TT}{hline 14}
{space 4}{space 0}{ralign 12:Variable}{space 1}{c |}{space 1}{ralign 8:Factor7}{space 1}{space 1}{ralign 8:Factor8}{space 1}{c |}{space 1}{ralign 12:Uniqueness}{space 1}
{space 4}{hline 13}{c   +}{hline 10}{hline 10}{c   +}{hline 14}
{space 4}{space 0}{ralign 12:gay9}{space 1}{c |}{space 1}{ralign 8:{res:{sf: -0.0282}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0008}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.6894}}}{space 1}
{space 4}{space 0}{ralign 12:tax9}{space 1}{c |}{space 1}{ralign 8:{res:{sf: -0.0225}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0012}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.5588}}}{space 1}
{space 4}{space 0}{ralign 12:script9}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.1076}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0141}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.8324}}}{space 1}
{space 4}{space 0}{ralign 12:health9}{space 1}{c |}{space 1}{ralign 8:{res:{sf: -0.0546}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0028}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.5977}}}{space 1}
{space 4}{space 0}{ralign 12:terror9}{space 1}{c |}{space 1}{ralign 8:{res:{sf: -0.0003}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0466}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.5836}}}{space 1}
{space 4}{space 0}{ralign 12:fisa9}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.0358}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0487}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.5829}}}{space 1}
{space 4}{space 0}{ralign 12:immigrants9}{space 1}{c |}{space 1}{ralign 8:{res:{sf: -0.0110}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0253}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.6113}}}{space 1}
{space 4}{space 0}{ralign 12:citizen9}{space 1}{c |}{space 1}{ralign 8:{res:{sf: -0.0124}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0193}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.5574}}}{space 1}
{space 4}{space 0}{ralign 12:ideo9}{space 1}{c |}{space 1}{ralign 8:{res:{sf:  0.0217}}}{space 1}{space 1}{ralign 8:{res:{sf:  0.0025}}}{space 1}{c |}{space 1}{center 12:{res:{sf:    0.7073}}}{space 1}
{space 4}{hline 13}{c  BT}{hline 10}{hline 10}{c  BT}{hline 14}

{com}. alpha gay9-ideo9, gen(canddiff9)

{txt}Test scale = mean(unstandardized items)

Average interitem covariance:{col 34}{res} .8416875
{txt}Number of items in the scale:{col 34}{res}        9
{txt}Scale reliability coefficient:{col 34}{res}   0.7079
{txt}
{com}. 
. 
. 
. ******
. *** affective
. *** parties
. ******
. 
. * wave 6
. 
. gen dem6 = . 
{txt}(4,240 missing values generated)

{com}. replace dem6 = 4 if W6E2 == 12 
{txt}(514 real changes made)

{com}. replace dem6 = 1 if W6E4 == 10
{txt}(171 real changes made)

{com}. replace dem6 = 2 if W6E4 == 11
{txt}(136 real changes made)

{com}. replace dem6 = 3 if W6E4 == 12
{txt}(31 real changes made)

{com}. replace dem6 = 5 if W6E3 == 12
{txt}(36 real changes made)

{com}. replace dem6 = 6 if W6E3 == 11
{txt}(289 real changes made)

{com}. replace dem6 = 7 if W6E3 == 10
{txt}(242 real changes made)

{com}. 
. 
. gen rep6 = . 
{txt}(4,240 missing values generated)

{com}. replace rep6 = 4 if W6E5 == 12 
{txt}(555 real changes made)

{com}. replace rep6 = 1 if W6E7 == 10
{txt}(223 real changes made)

{com}. replace rep6 = 2 if W6E7 == 11
{txt}(187 real changes made)

{com}. replace rep6 = 3 if W6E7 == 12
{txt}(43 real changes made)

{com}. replace rep6 = 5 if W6E6 == 12
{txt}(46 real changes made)

{com}. replace rep6 = 6 if W6E6 == 11
{txt}(247 real changes made)

{com}. replace rep6 = 7 if W6E6 == 10
{txt}(118 real changes made)

{com}. 
. 
. * wave 9
. 
. gen dem9 = . 
{txt}(4,240 missing values generated)

{com}. replace dem9 = 4 if W9E2 == 12 
{txt}(1,078 real changes made)

{com}. replace dem9 = 1 if W9E4 == 10
{txt}(337 real changes made)

{com}. replace dem9 = 2 if W9E4 == 11
{txt}(247 real changes made)

{com}. replace dem9 = 3 if W9E4 == 12
{txt}(56 real changes made)

{com}. replace dem9 = 5 if W9E3 == 12
{txt}(52 real changes made)

{com}. replace dem9 = 6 if W9E3 == 11
{txt}(494 real changes made)

{com}. replace dem9 = 7 if W9E3 == 10
{txt}(476 real changes made)

{com}. 
. 
. gen rep9 = . 
{txt}(4,240 missing values generated)

{com}. replace rep9 = 4 if W9E5 == 12 
{txt}(1,068 real changes made)

{com}. replace rep9 = 1 if W9E7 == 10
{txt}(473 real changes made)

{com}. replace rep9 = 2 if W9E7 == 11
{txt}(315 real changes made)

{com}. replace rep9 = 3 if W9E7 == 12
{txt}(57 real changes made)

{com}. replace rep9 = 5 if W9E6 == 12
{txt}(47 real changes made)

{com}. replace rep9 = 6 if W9E6 == 11
{txt}(466 real changes made)

{com}. replace rep9 = 7 if W9E6 == 10
{txt}(315 real changes made)

{com}. 
. ** candidates 
. 
. gen mccain6 = .
{txt}(4,240 missing values generated)

{com}. replace mccain6 = 4 if W6E14 == 12
{txt}(522 real changes made)

{com}. replace mccain6 = 1 if W6E16 == 10
{txt}(139 real changes made)

{com}. replace mccain6 = 2 if W6E16 == 11
{txt}(172 real changes made)

{com}. replace mccain6 = 3 if W6E16 == 12
{txt}(57 real changes made)

{com}. replace mccain6 = 5 if W6E15 == 12
{txt}(104 real changes made)

{com}. replace mccain6 = 6 if W6E15 == 11
{txt}(314 real changes made)

{com}. replace mccain6 = 7 if W6E15 == 10
{txt}(110 real changes made)

{com}. 
. gen mccain9 = .
{txt}(4,240 missing values generated)

{com}. replace mccain9 = 4 if W9E14 == 12
{txt}(883 real changes made)

{com}. replace mccain9 = 1 if W9E16 == 10
{txt}(271 real changes made)

{com}. replace mccain9 = 2 if W9E16 == 11
{txt}(255 real changes made)

{com}. replace mccain9 = 3 if W9E16 == 12
{txt}(84 real changes made)

{com}. replace mccain9 = 5 if W9E15 == 12
{txt}(140 real changes made)

{com}. replace mccain9 = 6 if W9E15 == 11
{txt}(740 real changes made)

{com}. replace mccain9 = 7 if W9E15 == 10
{txt}(367 real changes made)

{com}. 
. gen obama6 = .
{txt}(4,240 missing values generated)

{com}. replace obama6 = 4 if W6E38 == 12
{txt}(390 real changes made)

{com}. replace obama6 = 1 if W6E40 == 10
{txt}(260 real changes made)

{com}. replace obama6 = 2 if W6E40 == 11
{txt}(105 real changes made)

{com}. replace obama6 = 3 if W6E40 == 12
{txt}(28 real changes made)

{com}. replace obama6 = 5 if W6E39 == 12
{txt}(70 real changes made)

{com}. replace obama6 = 6 if W6E39 == 11
{txt}(268 real changes made)

{com}. replace obama6 = 7 if W6E39 == 10
{txt}(297 real changes made)

{com}. 
. gen obama9 = .
{txt}(4,240 missing values generated)

{com}. replace obama9 = 4 if W9E38 == 12
{txt}(729 real changes made)

{com}. replace obama9 = 1 if W9E40 == 10
{txt}(435 real changes made)

{com}. replace obama9 = 2 if W9E40 == 11
{txt}(224 real changes made)

{com}. replace obama9 = 3 if W9E40 == 12
{txt}(66 real changes made)

{com}. replace obama9 = 5 if W9E39 == 12
{txt}(116 real changes made)

{com}. replace obama9 = 6 if W9E39 == 11
{txt}(549 real changes made)

{com}. replace obama9 = 7 if W9E39 == 10
{txt}(623 real changes made)

{com}. 
. 
. ******************************
. *****
. ***** affective polarization
. *****
. ******************************
. 
. 
. gen party6 = abs(rep6-dem6)
{txt}(2,821 missing values generated)

{com}. gen party9 = abs(rep9-dem9)
{txt}(1,500 missing values generated)

{com}. gen cand6 = abs(mccain6-obama6)
{txt}(2,822 missing values generated)

{com}. gen cand9 = abs(mccain9-obama9)
{txt}(1,500 missing values generated)

{com}. 
. alpha party6 cand6, gen(affect6)

{txt}Test scale = mean(unstandardized items)

Average interitem covariance:{col 34}{res} 2.230268
{txt}Number of items in the scale:{col 34}{res}        2
{txt}Scale reliability coefficient:{col 34}{res}   0.6897
{txt}
{com}. alpha party9 cand9, gen(affect9)

{txt}Test scale = mean(unstandardized items)

Average interitem covariance:{col 34}{res} 2.595425
{txt}Number of items in the scale:{col 34}{res}        2
{txt}Scale reliability coefficient:{col 34}{res}   0.7309
{txt}
{com}. 
. 
. ********************************
. ********************************
. ********************************
. ********************************
. *** Control variables 
. ********************************
. ********************************
. ********************************
. ********************************
. 
. *** ideology 
. 
. gen ideology1 = .
{txt}(4,240 missing values generated)

{com}. replace ideology1 = -3 if W1N2 == 10
{txt}(117 real changes made)

{com}. replace ideology1 = -2 if W1N2 == 11
{txt}(238 real changes made)

{com}. replace ideology1 = -1 if W1N4 == 10
{txt}(181 real changes made)

{com}. replace ideology1 = 0 if W1N4 == 12
{txt}(354 real changes made)

{com}. replace ideology1 = 1 if W1N4 == 11
{txt}(139 real changes made)

{com}. replace ideology1 = 2 if W1N3 == 11
{txt}(386 real changes made)

{com}. replace ideology1 = 3 if W1N3 == 10
{txt}(198 real changes made)

{com}. 
. gen ideostrength1 = abs(ideology1)
{txt}(2,627 missing values generated)

{com}. 
. 
. 
. ** wave 6
. gen ideology6 = .
{txt}(4,240 missing values generated)

{com}. replace ideology6 = -3 if W6G2 == 10
{txt}(117 real changes made)

{com}. replace ideology6 = -2 if W6G2 == 11
{txt}(184 real changes made)

{com}. replace ideology6 = -1 if W6G4 == 10
{txt}(163 real changes made)

{com}. replace ideology6 = 0 if W6G4 == 12
{txt}(307 real changes made)

{com}. replace ideology6 = 1 if W6G4 == 11
{txt}(167 real changes made)

{com}. replace ideology6 = 2 if W6G3 == 11
{txt}(309 real changes made)

{com}. replace ideology6 = 3 if W6G3 == 10
{txt}(171 real changes made)

{com}. 
. gen ideostrength6 = abs(ideology6)
{txt}(2,822 missing values generated)

{com}. 
. *** ONLY HAVE PID FROM WAVE 1 (and wave 9)
. gen pid = .
{txt}(4,240 missing values generated)

{com}. replace pid = -3 if DER08W1 == 10
{txt}(327 real changes made)

{com}. replace pid = -2 if DER08W1 == 11
{txt}(240 real changes made)

{com}. replace pid = -1 if DER08W1 == 12
{txt}(172 real changes made)

{com}. replace pid = 0 if DER08W1 == 13
{txt}(200 real changes made)

{com}. replace pid = 1 if DER08W1 == 14
{txt}(149 real changes made)

{com}. replace pid = 2 if DER08W1 == 15
{txt}(249 real changes made)

{com}. replace pid = 3 if DER08W1 == 16
{txt}(277 real changes made)

{com}. 
. gen pidstrength = abs(pid)
{txt}(2,626 missing values generated)

{com}. 
. gen black = 0
{txt}
{com}. replace black = 1 if RRACEBLA == 11
{txt}(502 real changes made)

{com}. 
. gen age = .
{txt}(4,240 missing values generated)

{com}. replace age = RAGER if RAGER != 4
{txt}(4,194 real changes made)

{com}. replace age = age+7
{txt}(4,194 real changes made)

{com}. 
. gen female = .
{txt}(4,240 missing values generated)

{com}. replace female = 0 if DER01 == 10
{txt}(1,798 real changes made)

{com}. replace female = 1 if DER01 == 11
{txt}(2,442 real changes made)

{com}. 
. gen income = .
{txt}(4,240 missing values generated)

{com}. replace income = DER06 if DER06 > 9
{txt}(3,187 real changes made)

{com}. 
. gen education = .
{txt}(4,240 missing values generated)

{com}. replace education = DER05 if DER05 > 9
{txt}(3,222 real changes made)

{com}. 
. 
. ** political knowledfge
. 
. **** from WAVE 2 
. 
. gen k1 = 0
{txt}
{com}. gen k2 = 0
{txt}
{com}. gen k3 = 0
{txt}
{com}. gen k4 = 0
{txt}
{com}. gen k5 = 0
{txt}
{com}. gen k6 = 0
{txt}
{com}. 
. replace k1 = 1 if W2U2 == 12
{txt}(1,351 real changes made)

{com}. replace k1 = . if W2U2 < 10
{txt}(2,802 real changes made, 2,802 to missing)

{com}. 
. replace k2 = 1 if W2U3 == 16
{txt}(547 real changes made)

{com}. replace k2 = . if W2U3 < 10
{txt}(2,834 real changes made, 2,834 to missing)

{com}. 
. replace k3 = 1 if W2U4 == 12
{txt}(1,068 real changes made)

{com}. replace k3 = . if W2U4 < 10
{txt}(2,860 real changes made, 2,860 to missing)

{com}. 
. replace k4 = 1 if W2U5 == 12
{txt}(568 real changes made)

{com}. replace k4 = . if W2U5 < 10
{txt}(2,857 real changes made, 2,857 to missing)

{com}. 
. replace k5 = 1 if W2U6 == 12
{txt}(994 real changes made)

{com}. replace k5 = . if W2U6 < 10
{txt}(2,821 real changes made, 2,821 to missing)

{com}. 
. replace k6 = 1 if W2U7 == 11
{txt}(1,040 real changes made)

{com}. replace k6 = . if W2U7 < 10
{txt}(2,822 real changes made, 2,822 to missing)

{com}. 
. alpha k1-k6, gen(knowledge)

{txt}Test scale = mean(unstandardized items)

Average interitem covariance:{col 34}{res} .0331921
{txt}Number of items in the scale:{col 34}{res}        6
{txt}Scale reliability coefficient:{col 34}{res}   0.5663
{txt}
{com}. 
. 
. 
. ** issue extremity
. 
. **** from WAVE 1 
. 
. 
. * amend const for same sex
. gen gaySelf = .
{txt}(4,240 missing values generated)

{com}. replace gaySelf = 0 if W1P1 == 12
{txt}(388 real changes made)

{com}. replace gaySelf = 1 if W1P_O_2 == 10
{txt}(561 real changes made)

{com}. replace gaySelf = 2 if W1P_O_2 == 11
{txt}(135 real changes made)

{com}. replace gaySelf = 3 if W1P_O_2 == 12
{txt}(30 real changes made)

{com}. replace gaySelf = 5 if W1P_F_2 == 12
{txt}(21 real changes made)

{com}. replace gaySelf = 6 if W1P_F_2 == 11
{txt}(90 real changes made)

{com}. replace gaySelf = 7 if W1P_F_2 == 10
{txt}(384 real changes made)

{com}. 
. * tax the rich
. gen taxSelf = . 
{txt}(4,240 missing values generated)

{com}. replace taxSelf = 4 if W1P4 == 12
{txt}(362 real changes made)

{com}. replace taxSelf = 1 if W1P_O_5 == 10
{txt}(225 real changes made)

{com}. replace taxSelf = 2 if W1P_O_5 == 11
{txt}(114 real changes made)

{com}. replace taxSelf = 3 if W1P_O_5 == 12
{txt}(19 real changes made)

{com}. replace taxSelf = 5 if W1P_F_5 == 12
{txt}(44 real changes made)

{com}. replace taxSelf = 6 if W1P_F_5 == 11
{txt}(303 real changes made)

{com}. replace taxSelf = 7 if W1P_F_5 == 10
{txt}(544 real changes made)

{com}. 
. * gov pay for prescription drugs 
. gen scriptSelf = .
{txt}(4,240 missing values generated)

{com}. replace scriptSelf = 4 if W1P10 == 12
{txt}(226 real changes made)

{com}. replace scriptSelf = 1 if W1P_O_11 == 10
{txt}(67 real changes made)

{com}. replace scriptSelf = 2 if W1P_O_11 == 11
{txt}(89 real changes made)

{com}. replace scriptSelf= 3 if W1P_O_11 == 12
{txt}(24 real changes made)

{com}. replace scriptSelf = 5 if W1P_F_11 == 12
{txt}(43 real changes made)

{com}. replace scriptSelf = 6 if W1P_F_11 == 11
{txt}(301 real changes made)

{com}. replace scriptSelf = 7 if W1P_F_11 == 10
{txt}(860 real changes made)

{com}. 
. * gov pay for medical care
. gen healthSelf = .
{txt}(4,240 missing values generated)

{com}. replace healthSelf = 4 if W1P13 == 12
{txt}(355 real changes made)

{com}. replace healthSelf = 1 if W1P_O_14 == 10
{txt}(377 real changes made)

{com}. replace healthSelf = 2 if W1P_O_14 == 11
{txt}(195 real changes made)

{com}. replace healthSelf= 3 if W1P_O_14 == 12
{txt}(15 real changes made)

{com}. replace healthSelf = 5 if W1P_F_14 == 12
{txt}(22 real changes made)

{com}. replace healthSelf = 6 if W1P_F_14 == 11
{txt}(189 real changes made)

{com}. replace healthSelf = 7 if W1P_F_14 == 10
{txt}(459 real changes made)

{com}. 
. * detain terrorists 
. gen terrorSelf = .
{txt}(4,240 missing values generated)

{com}. replace terrorSelf = 4 if W1P16 == 12
{txt}(280 real changes made)

{com}. replace terrorSelf = 1 if W1P_O_17 == 10
{txt}(673 real changes made)

{com}. replace terrorSelf = 2 if W1P_O_17 == 11
{txt}(310 real changes made)

{com}. replace terrorSelf= 3 if W1P_O_17 == 12
{txt}(44 real changes made)

{com}. replace terrorSelf = 5 if W1P_F_17 == 12
{txt}(24 real changes made)

{com}. replace terrorSelf = 6 if W1P_F_17 == 11
{txt}(98 real changes made)

{com}. replace terrorSelf = 7 if W1P_F_17 == 10
{txt}(182 real changes made)

{com}. 
. * Need FISA warrant to wiretap terrorists? 
. gen fisaSelf = .
{txt}(4,240 missing values generated)

{com}. replace fisaSelf = 4 if W1P19 == 12
{txt}(214 real changes made)

{com}. replace fisaSelf = 1 if W1P_O_20 == 10
{txt}(255 real changes made)

{com}. replace fisaSelf = 2 if W1P_O_20 == 11
{txt}(172 real changes made)

{com}. replace fisaSelf = 3 if W1P_O_20 == 12
{txt}(13 real changes made)

{com}. replace fisaSelf = 5 if W1P_F_20 == 12
{txt}(43 real changes made)

{com}. replace fisaSelf = 6 if W1P_F_20 == 11
{txt}(256 real changes made)

{com}. replace fisaSelf = 7 if W1P_F_20 == 10
{txt}(658 real changes made)

{com}. 
. * Let immigrants work for 3 years, then send them back 
. gen immigrantsSelf = .
{txt}(4,240 missing values generated)

{com}. replace immigrantsSelf = 4 if W1P22 == 12
{txt}(328 real changes made)

{com}. replace immigrantsSelf = 1 if W1P_O_23 == 10
{txt}(672 real changes made)

{com}. replace immigrantsSelf = 2 if W1P_O_23 == 11
{txt}(196 real changes made)

{com}. replace immigrantsSelf = 3 if W1P_O_23 == 12
{txt}(25 real changes made)

{com}. replace immigrantsSelf = 5 if W1P_F_23 == 12
{txt}(30 real changes made)

{com}. replace immigrantsSelf = 6 if W1P_F_23 == 11
{txt}(180 real changes made)

{com}. replace immigrantsSelf = 7 if W1P_F_23 == 10
{txt}(181 real changes made)

{com}. 
. * allowing immigrants to become citizens
. gen citizenSelf = .
{txt}(4,240 missing values generated)

{com}. replace citizenSelf = 4 if W1P25 == 12
{txt}(282 real changes made)

{com}. replace citizenSelf = 1 if W1P_O_26 == 10
{txt}(472 real changes made)

{com}. replace citizenSelf = 2 if W1P_O_26 == 11
{txt}(152 real changes made)

{com}. replace citizenSelf = 3 if W1P_O_26 == 12
{txt}(20 real changes made)

{com}. replace citizenSelf = 5 if W1P_F_26 == 12
{txt}(55 real changes made)

{com}. replace citizenSelf = 6 if W1P_F_26 == 11
{txt}(328 real changes made)

{com}. replace citizenSelf = 7 if W1P_F_26 == 10
{txt}(303 real changes made)

{com}. 
. *recode
. foreach var of varlist gaySelf-citizenSelf{c -(} 
{txt}  2{com}.         recode `var' (1=-3) (2=-2) (3=-1) (4=0) (5=1) (6=2) (7=3)
{txt}  3{com}.         gen `var'2 = abs(`var')
{txt}  4{com}. {c )-}
{txt}(gaySelf: 1221 changes made)
(2,631 missing values generated)
(taxSelf: 1611 changes made)
(2,629 missing values generated)
(scriptSelf: 1610 changes made)
(2,630 missing values generated)
(healthSelf: 1612 changes made)
(2,628 missing values generated)
(terrorSelf: 1611 changes made)
(2,629 missing values generated)
(fisaSelf: 1611 changes made)
(2,629 missing values generated)
(immigrantsSelf: 1612 changes made)
(2,628 missing values generated)
(citizenSelf: 1612 changes made)
(2,628 missing values generated)

{com}. *
. 
. alpha gaySelf2-citizenSelf2, gen(issueextremity)

{txt}Test scale = mean(unstandardized items)

Average interitem covariance:{col 34}{res} .1776288
{txt}Number of items in the scale:{col 34}{res}        8
{txt}Scale reliability coefficient:{col 34}{res}   0.5578
{txt}
{com}. 
. 
. **** south
. 
. gen south = 0
{txt}
{com}. replace south = 1 if  W1XSTATE == 3
{txt}(23 real changes made)

{com}. replace south = 1 if  W1XSTATE == 4
{txt}(9 real changes made)

{com}. replace south = 1 if  W1XSTATE == 9
{txt}(5 real changes made)

{com}. replace south = 1 if  W1XSTATE == 10
{txt}(5 real changes made)

{com}. replace south = 1 if  W1XSTATE == 11
{txt}(81 real changes made)

{com}. replace south = 1 if  W1XSTATE == 12
{txt}(58 real changes made)

{com}. replace south = 1 if  W1XSTATE == 19
{txt}(27 real changes made)

{com}. replace south = 1 if  W1XSTATE == 20
{txt}(23 real changes made)

{com}. replace south = 1 if  W1XSTATE == 22
{txt}(24 real changes made)

{com}. replace south = 1 if  W1XSTATE == 27
{txt}(14 real changes made)

{com}. replace south = 1 if  W1XSTATE == 29
{txt}(49 real changes made)

{com}. replace south = 1 if  W1XSTATE == 38
{txt}(18 real changes made)

{com}. replace south = 1 if  W1XSTATE == 42
{txt}(20 real changes made)

{com}. replace south = 1 if  W1XSTATE == 44
{txt}(38 real changes made)

{com}. replace south = 1 if  W1XSTATE == 45
{txt}(101 real changes made)

{com}. replace south = 1 if  W1XSTATE == 47
{txt}(36 real changes made)

{com}. replace south = 1 if  W1XSTATE == 50
{txt}(9 real changes made)

{com}. 
. *** interest
. gen i1 = W6Y2 if W6Y2 > 9
{txt}(2,821 missing values generated)

{com}. gen i2 = W6Y3 if W6Y3 > 9
{txt}(2,820 missing values generated)

{com}. gen i3 = W6Y4 if W6Y4 > 9
{txt}(2,820 missing values generated)

{com}. gen i4 = W6Y5 if W6Y5 > 9
{txt}(2,820 missing values generated)

{com}. gen i5 = W6Y8 if W6Y8 > 9
{txt}(2,820 missing values generated)

{com}. gen i6 = W6Y9 if W6Y9 > 9
{txt}(2,820 missing values generated)

{com}. gen i7 = W6Y10 if W6Y10 > 9
{txt}(2,820 missing values generated)

{com}. 
. *recode
. foreach var of varlist i1-i7{c -(} 
{txt}  2{com}.         replace `var' = `var' - 9
{txt}  3{com}.         replace `var' = 6-`var'
{txt}  4{com}. {c )-}
{txt}(1,419 real changes made)
(1,238 real changes made)
(1,420 real changes made)
(1,103 real changes made)
(1,420 real changes made)
(1,153 real changes made)
(1,420 real changes made)
(1,062 real changes made)
(1,420 real changes made)
(1,124 real changes made)
(1,420 real changes made)
(1,254 real changes made)
(1,420 real changes made)
(1,277 real changes made)

{com}. *
. 
. alpha i1-i7, gen(interest6)

{txt}Test scale = mean(unstandardized items)

Average interitem covariance:{col 34}{res} .6117171
{txt}Number of items in the scale:{col 34}{res}        7
{txt}Scale reliability coefficient:{col 34}{res}   0.8509
{txt}
{com}. 
. 
. *rescale 0-1
. foreach v of var canddiff6 canddiff9 ideostrength1 ideostrength6 ///
>         age pidstrength income education issueextremity knowledge ////
>         affect6 affect9 interest6 ideo9 ideo6 tax6{c -(} 
{txt}  2{com}.         su `v', meanonly 
{txt}  3{com}.         gen `v'2 = (`v' - r(min))/(r(max) - r(min)) 
{txt}  4{com}. {c )-}
{txt}(2,826 missing values generated)
(1,512 missing values generated)
(2,627 missing values generated)
(2,822 missing values generated)
(46 missing values generated)
(2,626 missing values generated)
(1,053 missing values generated)
(1,018 missing values generated)
(2,621 missing values generated)
(2,791 missing values generated)
(2,821 missing values generated)
(1,499 missing values generated)
(2,820 missing values generated)
(1,519 missing values generated)
(2,844 missing values generated)
(3,142 missing values generated)

{com}. *
. 
. keep gaymccain6-interest62
{txt}
{com}.         
. ********************************************************************************
.         
. ****
. ** Supplemental Appendix Analyses
. ****    
. 
. * Model robustness
. sem (canddiff92 <- affect62 canddiff62) ///
>         (affect92 <- affect62 canddiff62), standardized 
{res}{txt}(2926 observations with missing values excluded)

Endogenous variables

{p 0 11 2}Observed:{space 2}{res}canddiff92 affect92{p_end}
{txt}
Exogenous variables

{p 0 11 2}Observed:{space 2}{res}affect62 canddiff62{p_end}
{txt}
Fitting target model:

Iteration 0:{space 3}log likelihood = {res: 634.96847}  
Iteration 1:{space 3}log likelihood = {res: 634.96847}  

{col 1}Structural equation model{col 49}Number of obs{col 67}= {res}     1,314
{txt}{col 1}Estimation method{col 20}= {res}ml
{txt}{col 1}Log likelihood{col 20}= {res} 634.96847

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}      OIM
{col 1}   Standardized{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}Structural     {col 17}{txt}{c |}
{space 2}{col 3}canddiff92   {col 17}{c |}
{space 7}affect62 {c |}{col 17}{res}{space 2} .2374141{col 29}{space 2} .0237011{col 40}{space 1}   10.02{col 49}{space 3}0.000{col 57}{space 4} .1909607{col 70}{space 3} .2838675
{txt}{space 5}canddiff62 {c |}{col 17}{res}{space 2} .4201494{col 29}{space 2} .0218057{col 40}{space 1}   19.27{col 49}{space 3}0.000{col 57}{space 4}  .377411{col 70}{space 3} .4628878
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 1.221354{col 29}{space 2} .0705176{col 40}{space 1}   17.32{col 49}{space 3}0.000{col 57}{space 4} 1.083142{col 70}{space 3} 1.359566
{space 2}{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}affect92     {col 17}{c |}
{space 7}affect62 {c |}{col 17}{res}{space 2} .7355415{col 29}{space 2}  .012523{col 40}{space 1}   58.74{col 49}{space 3}0.000{col 57}{space 4} .7109969{col 70}{space 3} .7600861
{txt}{space 5}canddiff62 {c |}{col 17}{res}{space 2} .0432493{col 29}{space 2} .0193482{col 40}{space 1}    2.24{col 49}{space 3}0.025{col 57}{space 4} .0053275{col 70}{space 3}  .081171
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .2992368{col 29}{space 2} .0456276{col 40}{space 1}    6.56{col 49}{space 3}0.000{col 57}{space 4} .2098083{col 70}{space 3} .3886653
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
var(e.canddi~92){c |}{col 17}{res}{space 2} .6989602{col 29}{space 2} .0195017{col 57}{space 4} .6617638{col 70}{space 3} .7382473
{txt}{space 1}var(e.affect92){c |}{col 17}{res}{space 2} .4353745{col 29}{space 2} .0152913{col 57}{space 4} .4064125{col 70}{space 3} .4664004
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
LR test of model vs. saturated: chi2({res:1})   = {res:    63.87}, Prob > chi2 = {res}0.0000
{txt}
{com}.         
. mrobust reg canddiff92 affect62 canddiff62 ideostrength62 pidstrength2 ///
>         issueextremity2 interest62 knowledge2 education2 age2 income2 female ///
>         black south
{res}{txt}note:  sample size varies across model specifications.
Listwise deletion:  3102 out of 4240 observations will not be used.

Calculating 4,096  models...
Estimated time is 61 seconds (1 minutes).
Each dot represents 1000 models calculated
....{res}
{txt}Linear regression;
Variable of interest {col 29}{res}affect62
{txt}Outcome variable  {col 29}{res}canddiff92{col 46}{txt}Number of observations{col 70}{res}     1138
{txt}Possible control terms   {col 29}{res}12{col 46}{txt}Mean R-squared{col 70}{res}     0.29
{txt}Number of models{col 29}{res}4,096          {col 46}{txt}Multicollinearity{col 70}{res}     0.31
{txt}{hline 79}
Model Robustness Statistics:{col 46}Significance Testing:

Mean(b){col 19}{res}   0.1557{col 46}{txt}Sign Stability{col 70}{res}      100%
{txt}Sampling SE{col 19}{res}   0.0178{col 46}{txt}Significance rate{col 70}{res}      100%
{txt}Modeling SE{col 19}{res}   0.0386{col 46}{txt}{hline 34}
Total SE{col 19}{res}   0.0425{col 46}{txt}Positive{col 70}{res}      100%
{txt}{hline 30}{col 46}Positive and Sig{col 70}{res}      100%
{txt}Robustness Ratio:{col 19}{res}   3.6644{col 46}{txt}Negative{col 70}{res}        0%
{txt}{col 46}Negative and Sig{col 70}{res}        0%
{txt}{hline 79}
Model Influence
{col 29}Marginal Effect{col 55}Percent Change
{col 26}of Variable Inclusion{col 56}From Mean(b)
{res}{txt}canddiff62{col 29}{res}  -0.0682{col 55}    -43.8{txt}%
{res}{txt}pidstrength2{col 29}{res}  -0.0262{col 55}    -16.8{txt}%
{res}{txt}ideostrength62{col 29}{res}  -0.0142{col 55}     -9.1{txt}%
{res}{txt}issueextremity2{col 29}{res}  -0.0126{col 55}     -8.1{txt}%
{res}{txt}interest62{col 29}{res}  -0.0099{col 55}     -6.4{txt}%
{res}{txt}knowledge2{col 29}{res}  -0.0039{col 55}     -2.5{txt}%
{res}{txt}income2{col 29}{res}   0.0037{col 55}      2.4{txt}%
{res}{txt}education2{col 29}{res}  -0.0035{col 55}     -2.2{txt}%
{res}{txt}black{col 29}{res}  -0.0020{col 55}     -1.3{txt}%
{res}{txt}female{col 29}{res}   0.0009{col 55}      0.6{txt}%
{res}{txt}south{col 29}{res}   0.0005{col 55}      0.3{txt}%
{res}{txt}age2{col 29}{res}  -0.0003{col 55}     -0.2{txt}%

Constant{col 29}{res}   0.2235
{txt}R-squared{col 29}{res}   0.9817
{txt}{hline 79}

This command took {res}52.7{txt} seconds ({res}.9{txt} minutes) to complete.
{res}{txt}
{com}.         
. mrobust reg     affect92 canddiff62 affect62 ideostrength62 pidstrength2 ///
>         issueextremity2 interest62 knowledge2 education2 age2 income2 female ///
>         black south
{res}{txt}note:  sample size varies across model specifications.
Listwise deletion:  3099 out of 4240 observations will not be used.

Calculating 4,096  models...
Estimated time is 51 seconds (.9 minutes).
Each dot represents 1000 models calculated
....{res}
{txt}Linear regression;
Variable of interest {col 29}{res}canddiff62
{txt}Outcome variable  {col 29}{res}affect92{col 46}{txt}Number of observations{col 70}{res}     1141
{txt}Possible control terms   {col 29}{res}12{col 46}{txt}Mean R-squared{col 70}{res}     0.41
{txt}Number of models{col 29}{res}4,096          {col 46}{txt}Multicollinearity{col 70}{res}     0.20
{txt}{hline 79}
Model Robustness Statistics:{col 46}Significance Testing:

Mean(b){col 19}{res}   0.1698{col 46}{txt}Sign Stability{col 70}{res}      100%
{txt}Sampling SE{col 19}{res}   0.0347{col 46}{txt}Significance rate{col 70}{res}       54%
{txt}Modeling SE{col 19}{res}   0.1371{col 46}{txt}{hline 34}
Total SE{col 19}{res}   0.1414{col 46}{txt}Positive{col 70}{res}      100%
{txt}{hline 30}{col 46}Positive and Sig{col 70}{res}       54%
{txt}Robustness Ratio:{col 19}{res}   1.2004{col 46}{txt}Negative{col 70}{res}        0%
{txt}{col 46}Negative and Sig{col 70}{res}        0%
{txt}{hline 79}
Model Influence
{col 29}Marginal Effect{col 55}Percent Change
{col 26}of Variable Inclusion{col 56}From Mean(b)
{res}{txt}affect62{col 29}{res}  -0.2600{col 55}   -153.2{txt}%
{res}{txt}pidstrength2{col 29}{res}  -0.0579{col 55}    -34.1{txt}%
{res}{txt}ideostrength62{col 29}{res}  -0.0325{col 55}    -19.1{txt}%
{res}{txt}issueextremity2{col 29}{res}  -0.0175{col 55}    -10.3{txt}%
{res}{txt}interest62{col 29}{res}  -0.0085{col 55}     -5.0{txt}%
{res}{txt}education2{col 29}{res}  -0.0023{col 55}     -1.3{txt}%
{res}{txt}female{col 29}{res}   0.0019{col 55}      1.1{txt}%
{res}{txt}south{col 29}{res}  -0.0016{col 55}     -0.9{txt}%
{res}{txt}black{col 29}{res}  -0.0010{col 55}     -0.6{txt}%
{res}{txt}age2{col 29}{res}   0.0007{col 55}      0.4{txt}%
{res}{txt}income2{col 29}{res}   0.0003{col 55}      0.2{txt}%
{res}{txt}knowledge2{col 29}{res}   0.0001{col 55}      0.0{txt}%

Constant{col 29}{res}   0.3588
{txt}R-squared{col 29}{res}   0.9630
{txt}{hline 79}

This command took {res}52.4{txt} seconds ({res}.9{txt} minutes) to complete.
{res}{txt}
{com}.         
.         
. * Disagregating affective polarization scales
. * replicates column 1 in Table A5       
. sem (canddiff92 <- party9 cand9 canddiff62 ideostrength62 pidstrength2 ///
>         issueextremity2 interest62 knowledge2 education2 age2 income2 female ///
>         black south) ///
>         (party9 cand9 <- party6 cand6 canddiff62 ideostrength62 pidstrength2 ///
>         issueextremity2 interest62 knowledge2 education2 age2 income2 female ///
>         black south), standardized 
{res}{txt}(3102 observations with missing values excluded)

Endogenous variables

{p 0 11 2}Observed:{space 2}{res}canddiff92 party9 cand9{p_end}
{txt}
Exogenous variables

{p 0 11 2}Observed:{space 2}{res}canddiff62 ideostrength62 pidstrength2 issueextremity2 interest62 knowledge2 education2 age2 income2 female black south party6 cand6{p_end}
{txt}
Fitting target model:

Iteration 0:{space 3}log likelihood = {res:-9039.1921}  
Iteration 1:{space 3}log likelihood = {res:-9039.1921}  

{col 1}Structural equation model{col 49}Number of obs{col 67}= {res}     1,138
{txt}{col 1}Estimation method{col 20}= {res}ml
{txt}{col 1}Log likelihood{col 20}= {res}-9039.1921

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}      OIM
{col 1}   Standardized{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}Structural     {col 17}{txt}{c |}
{space 2}{col 3}canddiff92   {col 17}{c |}
{space 9}party9 {c |}{col 17}{res}{space 2} .0767416{col 29}{space 2} .0325419{col 40}{space 1}    2.36{col 49}{space 3}0.018{col 57}{space 4} .0129607{col 70}{space 3} .1405225
{txt}{space 10}cand9 {c |}{col 17}{res}{space 2}  .169732{col 29}{space 2}  .029775{col 40}{space 1}    5.70{col 49}{space 3}0.000{col 57}{space 4} .1113742{col 70}{space 3} .2280899
{txt}{space 5}canddiff62 {c |}{col 17}{res}{space 2} .3559454{col 29}{space 2} .0236843{col 40}{space 1}   15.03{col 49}{space 3}0.000{col 57}{space 4}  .309525{col 70}{space 3} .4023657
{txt}{space 2}ideostreng~62 {c |}{col 17}{res}{space 2} .0408069{col 29}{space 2} .0265251{col 40}{space 1}    1.54{col 49}{space 3}0.124{col 57}{space 4}-.0111813{col 70}{space 3} .0927951
{txt}{space 3}pidstrength2 {c |}{col 17}{res}{space 2} .0645645{col 29}{space 2} .0276935{col 40}{space 1}    2.33{col 49}{space 3}0.020{col 57}{space 4} .0102863{col 70}{space 3} .1188427
{txt}{space 2}issueextrem~2 {c |}{col 17}{res}{space 2} .0991925{col 29}{space 2} .0246292{col 40}{space 1}    4.03{col 49}{space 3}0.000{col 57}{space 4} .0509202{col 70}{space 3} .1474647
{txt}{space 5}interest62 {c |}{col 17}{res}{space 2} .1139517{col 29}{space 2} .0244709{col 40}{space 1}    4.66{col 49}{space 3}0.000{col 57}{space 4} .0659896{col 70}{space 3} .1619139
{txt}{space 5}knowledge2 {c |}{col 17}{res}{space 2} .0669541{col 29}{space 2} .0267941{col 40}{space 1}    2.50{col 49}{space 3}0.012{col 57}{space 4} .0144387{col 70}{space 3} .1194695
{txt}{space 5}education2 {c |}{col 17}{res}{space 2} .0297408{col 29}{space 2} .0266995{col 40}{space 1}    1.11{col 49}{space 3}0.265{col 57}{space 4}-.0225893{col 70}{space 3} .0820708
{txt}{space 11}age2 {c |}{col 17}{res}{space 2}  -.00547{col 29}{space 2} .0243456{col 40}{space 1}   -0.22{col 49}{space 3}0.822{col 57}{space 4}-.0531864{col 70}{space 3} .0422465
{txt}{space 8}income2 {c |}{col 17}{res}{space 2} .0780349{col 29}{space 2} .0260039{col 40}{space 1}    3.00{col 49}{space 3}0.003{col 57}{space 4} .0270682{col 70}{space 3} .1290015
{txt}{space 9}female {c |}{col 17}{res}{space 2}-.0241827{col 29}{space 2} .0242466{col 40}{space 1}   -1.00{col 49}{space 3}0.319{col 57}{space 4}-.0717051{col 70}{space 3} .0233397
{txt}{space 10}black {c |}{col 17}{res}{space 2} .0383062{col 29}{space 2} .0241755{col 40}{space 1}    1.58{col 49}{space 3}0.113{col 57}{space 4} -.009077{col 70}{space 3} .0856894
{txt}{space 10}south {c |}{col 17}{res}{space 2}-.0284842{col 29}{space 2} .0235376{col 40}{space 1}   -1.21{col 49}{space 3}0.226{col 57}{space 4} -.074617{col 70}{space 3} .0176487
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .2199384{col 29}{space 2} .1437716{col 40}{space 1}    1.53{col 49}{space 3}0.126{col 57}{space 4}-.0618488{col 70}{space 3} .5017255
{space 2}{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}party9       {col 17}{c |}
{space 5}canddiff62 {c |}{col 17}{res}{space 2} .0199303{col 29}{space 2} .0212446{col 40}{space 1}    0.94{col 49}{space 3}0.348{col 57}{space 4}-.0217084{col 70}{space 3} .0615691
{txt}{space 2}ideostreng~62 {c |}{col 17}{res}{space 2} .0398978{col 29}{space 2} .0218787{col 40}{space 1}    1.82{col 49}{space 3}0.068{col 57}{space 4}-.0029837{col 70}{space 3} .0827793
{txt}{space 3}pidstrength2 {c |}{col 17}{res}{space 2} .1568926{col 29}{space 2} .0224572{col 40}{space 1}    6.99{col 49}{space 3}0.000{col 57}{space 4} .1128773{col 70}{space 3} .2009078
{txt}{space 2}issueextrem~2 {c |}{col 17}{res}{space 2} .0510306{col 29}{space 2} .0202846{col 40}{space 1}    2.52{col 49}{space 3}0.012{col 57}{space 4} .0112735{col 70}{space 3} .0907878
{txt}{space 5}interest62 {c |}{col 17}{res}{space 2} .0122576{col 29}{space 2} .0202868{col 40}{space 1}    0.60{col 49}{space 3}0.546{col 57}{space 4}-.0275037{col 70}{space 3}  .052019
{txt}{space 5}knowledge2 {c |}{col 17}{res}{space 2} .0062486{col 29}{space 2} .0221426{col 40}{space 1}    0.28{col 49}{space 3}0.778{col 57}{space 4}-.0371501{col 70}{space 3} .0496473
{txt}{space 5}education2 {c |}{col 17}{res}{space 2} .0275385{col 29}{space 2} .0219464{col 40}{space 1}    1.25{col 49}{space 3}0.210{col 57}{space 4}-.0154755{col 70}{space 3} .0705526
{txt}{space 11}age2 {c |}{col 17}{res}{space 2}-.0205587{col 29}{space 2} .0200867{col 40}{space 1}   -1.02{col 49}{space 3}0.306{col 57}{space 4} -.059928{col 70}{space 3} .0188105
{txt}{space 8}income2 {c |}{col 17}{res}{space 2}-.0042608{col 29}{space 2}  .021499{col 40}{space 1}   -0.20{col 49}{space 3}0.843{col 57}{space 4} -.046398{col 70}{space 3} .0378764
{txt}{space 9}female {c |}{col 17}{res}{space 2} .0110034{col 29}{space 2} .0199759{col 40}{space 1}    0.55{col 49}{space 3}0.582{col 57}{space 4}-.0281486{col 70}{space 3} .0501554
{txt}{space 10}black {c |}{col 17}{res}{space 2}-.0247706{col 29}{space 2} .0200276{col 40}{space 1}   -1.24{col 49}{space 3}0.216{col 57}{space 4}-.0640241{col 70}{space 3} .0144828
{txt}{space 10}south {c |}{col 17}{res}{space 2} .0078402{col 29}{space 2} .0193826{col 40}{space 1}    0.40{col 49}{space 3}0.686{col 57}{space 4}-.0301491{col 70}{space 3} .0458295
{txt}{space 9}party6 {c |}{col 17}{res}{space 2} .5612338{col 29}{space 2} .0224813{col 40}{space 1}   24.96{col 49}{space 3}0.000{col 57}{space 4} .5171714{col 70}{space 3} .6052963
{txt}{space 10}cand6 {c |}{col 17}{res}{space 2} .1268476{col 29}{space 2} .0231151{col 40}{space 1}    5.49{col 49}{space 3}0.000{col 57}{space 4} .0815428{col 70}{space 3} .1721523
{txt}{space 10}_cons {c |}{col 17}{res}{space 2}-.2927513{col 29}{space 2} .1150838{col 40}{space 1}   -2.54{col 49}{space 3}0.011{col 57}{space 4}-.5183114{col 70}{space 3}-.0671913
{space 2}{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}cand9        {col 17}{c |}
{space 5}canddiff62 {c |}{col 17}{res}{space 2} .0139565{col 29}{space 2} .0239419{col 40}{space 1}    0.58{col 49}{space 3}0.560{col 57}{space 4}-.0329688{col 70}{space 3} .0608818
{txt}{space 2}ideostreng~62 {c |}{col 17}{res}{space 2} .0119266{col 29}{space 2} .0246705{col 40}{space 1}    0.48{col 49}{space 3}0.629{col 57}{space 4}-.0364267{col 70}{space 3} .0602799
{txt}{space 3}pidstrength2 {c |}{col 17}{res}{space 2} .1072541{col 29}{space 2} .0254443{col 40}{space 1}    4.22{col 49}{space 3}0.000{col 57}{space 4} .0573842{col 70}{space 3} .1571241
{txt}{space 2}issueextrem~2 {c |}{col 17}{res}{space 2}   .05804{col 29}{space 2} .0228466{col 40}{space 1}    2.54{col 49}{space 3}0.011{col 57}{space 4} .0132614{col 70}{space 3} .1028186
{txt}{space 5}interest62 {c |}{col 17}{res}{space 2} .0456387{col 29}{space 2} .0228355{col 40}{space 1}    2.00{col 49}{space 3}0.046{col 57}{space 4} .0008819{col 70}{space 3} .0903955
{txt}{space 5}knowledge2 {c |}{col 17}{res}{space 2}-.0263704{col 29}{space 2} .0249438{col 40}{space 1}   -1.06{col 49}{space 3}0.290{col 57}{space 4}-.0752593{col 70}{space 3} .0225186
{txt}{space 5}education2 {c |}{col 17}{res}{space 2}-.0473082{col 29}{space 2} .0247125{col 40}{space 1}   -1.91{col 49}{space 3}0.056{col 57}{space 4}-.0957438{col 70}{space 3} .0011275
{txt}{space 11}age2 {c |}{col 17}{res}{space 2}-.0087749{col 29}{space 2} .0226391{col 40}{space 1}   -0.39{col 49}{space 3}0.698{col 57}{space 4}-.0531467{col 70}{space 3} .0355969
{txt}{space 8}income2 {c |}{col 17}{res}{space 2} .0275396{col 29}{space 2} .0242173{col 40}{space 1}    1.14{col 49}{space 3}0.255{col 57}{space 4}-.0199255{col 70}{space 3} .0750047
{txt}{space 9}female {c |}{col 17}{res}{space 2} .0158755{col 29}{space 2} .0225082{col 40}{space 1}    0.71{col 49}{space 3}0.481{col 57}{space 4}-.0282397{col 70}{space 3} .0599907
{txt}{space 10}black {c |}{col 17}{res}{space 2}-.0033186{col 29}{space 2} .0225757{col 40}{space 1}   -0.15{col 49}{space 3}0.883{col 57}{space 4}-.0475662{col 70}{space 3}  .040929
{txt}{space 10}south {c |}{col 17}{res}{space 2} .0113101{col 29}{space 2} .0218405{col 40}{space 1}    0.52{col 49}{space 3}0.605{col 57}{space 4}-.0314966{col 70}{space 3} .0541167
{txt}{space 9}party6 {c |}{col 17}{res}{space 2} .1768086{col 29}{space 2} .0282713{col 40}{space 1}    6.25{col 49}{space 3}0.000{col 57}{space 4} .1213979{col 70}{space 3} .2322193
{txt}{space 10}cand6 {c |}{col 17}{res}{space 2} .5029441{col 29}{space 2} .0232331{col 40}{space 1}   21.65{col 49}{space 3}0.000{col 57}{space 4} .4574081{col 70}{space 3}   .54848
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .0740497{col 29}{space 2}  .131462{col 40}{space 1}    0.56{col 49}{space 3}0.573{col 57}{space 4}-.1836111{col 70}{space 3} .3317106
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
var(e.canddi~92){c |}{col 17}{res}{space 2} .6114894{col 29}{space 2} .0204358{col 57}{space 4} .5727196{col 70}{space 3} .6528837
{txt}{space 3}var(e.party9){c |}{col 17}{res}{space 2} .4142404{col 29}{space 2} .0158058{col 57}{space 4} .3843916{col 70}{space 3} .4464071
{txt}{space 4}var(e.cand9){c |}{col 17}{res}{space 2} .5260052{col 29}{space 2} .0187542{col 57}{space 4} .4905025{col 70}{space 3} .5640775
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
LR test of model vs. saturated: chi2({res:3})   = {res:   154.86}, Prob > chi2 = {res}0.0000
{txt}
{com}.         
. * replicates columns 2 and 3 in Table A5
. sem (canddiff92 <- party6 cand6 canddiff62 ideostrength62 pidstrength2 ///
>         issueextremity2 interest62 knowledge2 education2 age2 income2 female ///
>         black south) ///
>         (party9 cand9 <- party6 cand6 canddiff62 ideostrength62 pidstrength2 ///
>         issueextremity2 interest62 knowledge2 education2 age2 income2 female ///
>         black south), standardized 
{res}{txt}(3102 observations with missing values excluded)

Endogenous variables

{p 0 11 2}Observed:{space 2}{res}canddiff92 party9 cand9{p_end}
{txt}
Exogenous variables

{p 0 11 2}Observed:{space 2}{res}party6 cand6 canddiff62 ideostrength62 pidstrength2 issueextremity2 interest62 knowledge2 education2 age2 income2 female black south{p_end}
{txt}
Fitting target model:

Iteration 0:{space 3}log likelihood = {res:-9057.3354}  
Iteration 1:{space 3}log likelihood = {res:-9057.3354}  

{col 1}Structural equation model{col 49}Number of obs{col 67}= {res}     1,138
{txt}{col 1}Estimation method{col 20}= {res}ml
{txt}{col 1}Log likelihood{col 20}= {res}-9057.3354

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}      OIM
{col 1}   Standardized{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}Structural     {col 17}{txt}{c |}
{space 2}{col 3}canddiff92   {col 17}{c |}
{space 9}party6 {c |}{col 17}{res}{space 2} .0886695{col 29}{space 2} .0311645{col 40}{space 1}    2.85{col 49}{space 3}0.004{col 57}{space 4} .0275882{col 70}{space 3} .1497509
{txt}{space 10}cand6 {c |}{col 17}{res}{space 2} .0920964{col 29}{space 2} .0285542{col 40}{space 1}    3.23{col 49}{space 3}0.001{col 57}{space 4} .0361312{col 70}{space 3} .1480616
{txt}{space 5}canddiff62 {c |}{col 17}{res}{space 2} .3570397{col 29}{space 2} .0243432{col 40}{space 1}   14.67{col 49}{space 3}0.000{col 57}{space 4}  .309328{col 70}{space 3} .4047514
{txt}{space 2}ideostreng~62 {c |}{col 17}{res}{space 2} .0437999{col 29}{space 2} .0269449{col 40}{space 1}    1.63{col 49}{space 3}0.104{col 57}{space 4}-.0090111{col 70}{space 3} .0966109
{txt}{space 3}pidstrength2 {c |}{col 17}{res}{space 2} .0892059{col 29}{space 2} .0278552{col 40}{space 1}    3.20{col 49}{space 3}0.001{col 57}{space 4} .0346108{col 70}{space 3}  .143801
{txt}{space 2}issueextrem~2 {c |}{col 17}{res}{space 2}  .111927{col 29}{space 2} .0248397{col 40}{space 1}    4.51{col 49}{space 3}0.000{col 57}{space 4} .0632421{col 70}{space 3} .1606119
{txt}{space 5}interest62 {c |}{col 17}{res}{space 2} .1224582{col 29}{space 2} .0247733{col 40}{space 1}    4.94{col 49}{space 3}0.000{col 57}{space 4} .0739034{col 70}{space 3} .1710129
{txt}{space 5}knowledge2 {c |}{col 17}{res}{space 2} .0616651{col 29}{space 2} .0272259{col 40}{space 1}    2.26{col 49}{space 3}0.024{col 57}{space 4} .0083033{col 70}{space 3} .1150269
{txt}{space 5}education2 {c |}{col 17}{res}{space 2} .0232003{col 29}{space 2} .0270365{col 40}{space 1}    0.86{col 49}{space 3}0.391{col 57}{space 4}-.0297902{col 70}{space 3} .0761908
{txt}{space 11}age2 {c |}{col 17}{res}{space 2}-.0078262{col 29}{space 2} .0247484{col 40}{space 1}   -0.32{col 49}{space 3}0.752{col 57}{space 4}-.0563322{col 70}{space 3} .0406798
{txt}{space 8}income2 {c |}{col 17}{res}{space 2} .0830892{col 29}{space 2} .0263887{col 40}{space 1}    3.15{col 49}{space 3}0.002{col 57}{space 4} .0313683{col 70}{space 3} .1348101
{txt}{space 9}female {c |}{col 17}{res}{space 2}-.0205282{col 29}{space 2} .0246025{col 40}{space 1}   -0.83{col 49}{space 3}0.404{col 57}{space 4}-.0687481{col 70}{space 3} .0276917
{txt}{space 10}black {c |}{col 17}{res}{space 2} .0348447{col 29}{space 2} .0246612{col 40}{space 1}    1.41{col 49}{space 3}0.158{col 57}{space 4}-.0134905{col 70}{space 3} .0831798
{txt}{space 10}south {c |}{col 17}{res}{space 2}-.0263269{col 29}{space 2} .0238666{col 40}{space 1}   -1.10{col 49}{space 3}0.270{col 57}{space 4}-.0731046{col 70}{space 3} .0204507
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .2146729{col 29}{space 2} .1451691{col 40}{space 1}    1.48{col 49}{space 3}0.139{col 57}{space 4}-.0698533{col 70}{space 3} .4991991
{space 2}{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}party9       {col 17}{c |}
{space 9}party6 {c |}{col 17}{res}{space 2} .5612338{col 29}{space 2} .0224813{col 40}{space 1}   24.96{col 49}{space 3}0.000{col 57}{space 4} .5171714{col 70}{space 3} .6052963
{txt}{space 10}cand6 {c |}{col 17}{res}{space 2} .1268476{col 29}{space 2} .0231151{col 40}{space 1}    5.49{col 49}{space 3}0.000{col 57}{space 4} .0815428{col 70}{space 3} .1721523
{txt}{space 5}canddiff62 {c |}{col 17}{res}{space 2} .0199303{col 29}{space 2} .0212446{col 40}{space 1}    0.94{col 49}{space 3}0.348{col 57}{space 4}-.0217084{col 70}{space 3} .0615691
{txt}{space 2}ideostreng~62 {c |}{col 17}{res}{space 2} .0398978{col 29}{space 2} .0218787{col 40}{space 1}    1.82{col 49}{space 3}0.068{col 57}{space 4}-.0029837{col 70}{space 3} .0827793
{txt}{space 3}pidstrength2 {c |}{col 17}{res}{space 2} .1568926{col 29}{space 2} .0224572{col 40}{space 1}    6.99{col 49}{space 3}0.000{col 57}{space 4} .1128773{col 70}{space 3} .2009078
{txt}{space 2}issueextrem~2 {c |}{col 17}{res}{space 2} .0510306{col 29}{space 2} .0202846{col 40}{space 1}    2.52{col 49}{space 3}0.012{col 57}{space 4} .0112735{col 70}{space 3} .0907878
{txt}{space 5}interest62 {c |}{col 17}{res}{space 2} .0122576{col 29}{space 2} .0202868{col 40}{space 1}    0.60{col 49}{space 3}0.546{col 57}{space 4}-.0275037{col 70}{space 3}  .052019
{txt}{space 5}knowledge2 {c |}{col 17}{res}{space 2} .0062486{col 29}{space 2} .0221426{col 40}{space 1}    0.28{col 49}{space 3}0.778{col 57}{space 4}-.0371501{col 70}{space 3} .0496473
{txt}{space 5}education2 {c |}{col 17}{res}{space 2} .0275385{col 29}{space 2} .0219464{col 40}{space 1}    1.25{col 49}{space 3}0.210{col 57}{space 4}-.0154755{col 70}{space 3} .0705526
{txt}{space 11}age2 {c |}{col 17}{res}{space 2}-.0205587{col 29}{space 2} .0200867{col 40}{space 1}   -1.02{col 49}{space 3}0.306{col 57}{space 4} -.059928{col 70}{space 3} .0188105
{txt}{space 8}income2 {c |}{col 17}{res}{space 2}-.0042608{col 29}{space 2}  .021499{col 40}{space 1}   -0.20{col 49}{space 3}0.843{col 57}{space 4} -.046398{col 70}{space 3} .0378764
{txt}{space 9}female {c |}{col 17}{res}{space 2} .0110034{col 29}{space 2} .0199759{col 40}{space 1}    0.55{col 49}{space 3}0.582{col 57}{space 4}-.0281486{col 70}{space 3} .0501554
{txt}{space 10}black {c |}{col 17}{res}{space 2}-.0247706{col 29}{space 2} .0200276{col 40}{space 1}   -1.24{col 49}{space 3}0.216{col 57}{space 4}-.0640241{col 70}{space 3} .0144828
{txt}{space 10}south {c |}{col 17}{res}{space 2} .0078402{col 29}{space 2} .0193826{col 40}{space 1}    0.40{col 49}{space 3}0.686{col 57}{space 4}-.0301491{col 70}{space 3} .0458295
{txt}{space 10}_cons {c |}{col 17}{res}{space 2}-.2927513{col 29}{space 2} .1150838{col 40}{space 1}   -2.54{col 49}{space 3}0.011{col 57}{space 4}-.5183114{col 70}{space 3}-.0671913
{space 2}{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}cand9        {col 17}{c |}
{space 9}party6 {c |}{col 17}{res}{space 2} .1768086{col 29}{space 2} .0282713{col 40}{space 1}    6.25{col 49}{space 3}0.000{col 57}{space 4} .1213979{col 70}{space 3} .2322193
{txt}{space 10}cand6 {c |}{col 17}{res}{space 2} .5029441{col 29}{space 2} .0232331{col 40}{space 1}   21.65{col 49}{space 3}0.000{col 57}{space 4} .4574081{col 70}{space 3}   .54848
{txt}{space 5}canddiff62 {c |}{col 17}{res}{space 2} .0139565{col 29}{space 2} .0239419{col 40}{space 1}    0.58{col 49}{space 3}0.560{col 57}{space 4}-.0329688{col 70}{space 3} .0608818
{txt}{space 2}ideostreng~62 {c |}{col 17}{res}{space 2} .0119266{col 29}{space 2} .0246705{col 40}{space 1}    0.48{col 49}{space 3}0.629{col 57}{space 4}-.0364267{col 70}{space 3} .0602799
{txt}{space 3}pidstrength2 {c |}{col 17}{res}{space 2} .1072541{col 29}{space 2} .0254443{col 40}{space 1}    4.22{col 49}{space 3}0.000{col 57}{space 4} .0573842{col 70}{space 3} .1571241
{txt}{space 2}issueextrem~2 {c |}{col 17}{res}{space 2}   .05804{col 29}{space 2} .0228466{col 40}{space 1}    2.54{col 49}{space 3}0.011{col 57}{space 4} .0132614{col 70}{space 3} .1028186
{txt}{space 5}interest62 {c |}{col 17}{res}{space 2} .0456387{col 29}{space 2} .0228355{col 40}{space 1}    2.00{col 49}{space 3}0.046{col 57}{space 4} .0008819{col 70}{space 3} .0903955
{txt}{space 5}knowledge2 {c |}{col 17}{res}{space 2}-.0263704{col 29}{space 2} .0249438{col 40}{space 1}   -1.06{col 49}{space 3}0.290{col 57}{space 4}-.0752593{col 70}{space 3} .0225186
{txt}{space 5}education2 {c |}{col 17}{res}{space 2}-.0473082{col 29}{space 2} .0247125{col 40}{space 1}   -1.91{col 49}{space 3}0.056{col 57}{space 4}-.0957438{col 70}{space 3} .0011275
{txt}{space 11}age2 {c |}{col 17}{res}{space 2}-.0087749{col 29}{space 2} .0226391{col 40}{space 1}   -0.39{col 49}{space 3}0.698{col 57}{space 4}-.0531467{col 70}{space 3} .0355969
{txt}{space 8}income2 {c |}{col 17}{res}{space 2} .0275396{col 29}{space 2} .0242173{col 40}{space 1}    1.14{col 49}{space 3}0.255{col 57}{space 4}-.0199255{col 70}{space 3} .0750047
{txt}{space 9}female {c |}{col 17}{res}{space 2} .0158755{col 29}{space 2} .0225082{col 40}{space 1}    0.71{col 49}{space 3}0.481{col 57}{space 4}-.0282397{col 70}{space 3} .0599907
{txt}{space 10}black {c |}{col 17}{res}{space 2}-.0033186{col 29}{space 2} .0225757{col 40}{space 1}   -0.15{col 49}{space 3}0.883{col 57}{space 4}-.0475662{col 70}{space 3}  .040929
{txt}{space 10}south {c |}{col 17}{res}{space 2} .0113101{col 29}{space 2} .0218405{col 40}{space 1}    0.52{col 49}{space 3}0.605{col 57}{space 4}-.0314966{col 70}{space 3} .0541167
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .0740497{col 29}{space 2}  .131462{col 40}{space 1}    0.56{col 49}{space 3}0.573{col 57}{space 4}-.1836111{col 70}{space 3} .3317106
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
var(e.canddi~92){c |}{col 17}{res}{space 2} .6285788{col 29}{space 2} .0204947{col 57}{space 4} .5896665{col 70}{space 3} .6700589
{txt}{space 3}var(e.party9){c |}{col 17}{res}{space 2} .4142404{col 29}{space 2} .0158058{col 57}{space 4} .3843916{col 70}{space 3} .4464071
{txt}{space 4}var(e.cand9){c |}{col 17}{res}{space 2} .5260052{col 29}{space 2} .0187542{col 57}{space 4} .4905025{col 70}{space 3} .5640775
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
LR test of model vs. saturated: chi2({res:3})   = {res:   191.15}, Prob > chi2 = {res}0.0000
{txt}
{com}.         
. **** here       
. * Partisan affect only
. sem (canddiff92 <- party9 canddiff62 ideostrength62 pidstrength2 ///
>         issueextremity2 interest62 knowledge2 education2 age2 income2 female ///
>         black south) ///
>         (party9 <- party6 canddiff62 ideostrength62 pidstrength2 ///
>         issueextremity2 interest62 knowledge2 education2 age2 income2 female ///
>         black south), standardized      
{res}{txt}(3102 observations with missing values excluded)

Endogenous variables

{p 0 11 2}Observed:{space 2}{res}canddiff92 party9{p_end}
{txt}
Exogenous variables

{p 0 11 2}Observed:{space 2}{res}canddiff62 ideostrength62 pidstrength2 issueextremity2 interest62 knowledge2 education2 age2 income2 female black south party6{p_end}
{txt}
Fitting target model:

Iteration 0:{space 3}log likelihood = {res:-4859.4725}  
Iteration 1:{space 3}log likelihood = {res:-4859.4725}  

{col 1}Structural equation model{col 49}Number of obs{col 67}= {res}     1,138
{txt}{col 1}Estimation method{col 20}= {res}ml
{txt}{col 1}Log likelihood{col 20}= {res}-4859.4725

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}      OIM
{col 1}   Standardized{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}Structural     {col 17}{txt}{c |}
{space 2}{col 3}canddiff92   {col 17}{c |}
{space 9}party9 {c |}{col 17}{res}{space 2} .1706374{col 29}{space 2} .0280258{col 40}{space 1}    6.09{col 49}{space 3}0.000{col 57}{space 4} .1157079{col 70}{space 3} .2255669
{txt}{space 5}canddiff62 {c |}{col 17}{res}{space 2} .3667795{col 29}{space 2} .0237878{col 40}{space 1}   15.42{col 49}{space 3}0.000{col 57}{space 4} .3201563{col 70}{space 3} .4134027
{txt}{space 2}ideostreng~62 {c |}{col 17}{res}{space 2} .0415539{col 29}{space 2} .0268408{col 40}{space 1}    1.55{col 49}{space 3}0.122{col 57}{space 4}-.0110532{col 70}{space 3} .0941609
{txt}{space 3}pidstrength2 {c |}{col 17}{res}{space 2} .0721095{col 29}{space 2} .0279925{col 40}{space 1}    2.58{col 49}{space 3}0.010{col 57}{space 4} .0172451{col 70}{space 3} .1269739
{txt}{space 2}issueextrem~2 {c |}{col 17}{res}{space 2} .1087951{col 29}{space 2}  .024836{col 40}{space 1}    4.38{col 49}{space 3}0.000{col 57}{space 4} .0601175{col 70}{space 3} .1574727
{txt}{space 5}interest62 {c |}{col 17}{res}{space 2} .1262574{col 29}{space 2}  .024615{col 40}{space 1}    5.13{col 49}{space 3}0.000{col 57}{space 4} .0780129{col 70}{space 3} .1745018
{txt}{space 5}knowledge2 {c |}{col 17}{res}{space 2} .0584975{col 29}{space 2} .0270855{col 40}{space 1}    2.16{col 49}{space 3}0.031{col 57}{space 4} .0054109{col 70}{space 3}  .111584
{txt}{space 5}education2 {c |}{col 17}{res}{space 2} .0220512{col 29}{space 2} .0269866{col 40}{space 1}    0.82{col 49}{space 3}0.414{col 57}{space 4}-.0308415{col 70}{space 3} .0749439
{txt}{space 11}age2 {c |}{col 17}{res}{space 2}-.0002529{col 29}{space 2} .0246156{col 40}{space 1}   -0.01{col 49}{space 3}0.992{col 57}{space 4}-.0484985{col 70}{space 3} .0479927
{txt}{space 8}income2 {c |}{col 17}{res}{space 2} .0801947{col 29}{space 2} .0262986{col 40}{space 1}    3.05{col 49}{space 3}0.002{col 57}{space 4} .0286503{col 70}{space 3}  .131739
{txt}{space 9}female {c |}{col 17}{res}{space 2}-.0186948{col 29}{space 2} .0245162{col 40}{space 1}   -0.76{col 49}{space 3}0.446{col 57}{space 4}-.0667456{col 70}{space 3}  .029356
{txt}{space 10}black {c |}{col 17}{res}{space 2} .0468004{col 29}{space 2} .0244025{col 40}{space 1}    1.92{col 49}{space 3}0.055{col 57}{space 4}-.0010277{col 70}{space 3} .0946284
{txt}{space 10}south {c |}{col 17}{res}{space 2}-.0259369{col 29}{space 2} .0238122{col 40}{space 1}   -1.09{col 49}{space 3}0.276{col 57}{space 4}-.0726081{col 70}{space 3} .0207342
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .2595174{col 29}{space 2} .1455762{col 40}{space 1}    1.78{col 49}{space 3}0.075{col 57}{space 4}-.0258068{col 70}{space 3} .5448415
{space 2}{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}party9       {col 17}{c |}
{space 5}canddiff62 {c |}{col 17}{res}{space 2} .0361184{col 29}{space 2} .0212994{col 40}{space 1}    1.70{col 49}{space 3}0.090{col 57}{space 4}-.0056276{col 70}{space 3} .0778644
{txt}{space 2}ideostreng~62 {c |}{col 17}{res}{space 2} .0417359{col 29}{space 2} .0221583{col 40}{space 1}    1.88{col 49}{space 3}0.060{col 57}{space 4}-.0016936{col 70}{space 3} .0851654
{txt}{space 3}pidstrength2 {c |}{col 17}{res}{space 2} .1573629{col 29}{space 2} .0227458{col 40}{space 1}    6.92{col 49}{space 3}0.000{col 57}{space 4}  .112782{col 70}{space 3} .2019438
{txt}{space 2}issueextrem~2 {c |}{col 17}{res}{space 2} .0581081{col 29}{space 2}  .020497{col 40}{space 1}    2.83{col 49}{space 3}0.005{col 57}{space 4} .0179346{col 70}{space 3} .0982815
{txt}{space 5}interest62 {c |}{col 17}{res}{space 2} .0224248{col 29}{space 2}  .020459{col 40}{space 1}    1.10{col 49}{space 3}0.273{col 57}{space 4}-.0176741{col 70}{space 3} .0625238
{txt}{space 5}knowledge2 {c |}{col 17}{res}{space 2}-.0006808{col 29}{space 2} .0223933{col 40}{space 1}   -0.03{col 49}{space 3}0.976{col 57}{space 4}-.0445708{col 70}{space 3} .0432092
{txt}{space 5}education2 {c |}{col 17}{res}{space 2} .0318385{col 29}{space 2} .0222141{col 40}{space 1}    1.43{col 49}{space 3}0.152{col 57}{space 4}-.0117003{col 70}{space 3} .0753773
{txt}{space 11}age2 {c |}{col 17}{res}{space 2}-.0116831{col 29}{space 2} .0202836{col 40}{space 1}   -0.58{col 49}{space 3}0.565{col 57}{space 4}-.0514382{col 70}{space 3}  .028072
{txt}{space 8}income2 {c |}{col 17}{res}{space 2}-.0077664{col 29}{space 2} .0217677{col 40}{space 1}   -0.36{col 49}{space 3}0.721{col 57}{space 4}-.0504304{col 70}{space 3} .0348975
{txt}{space 9}female {c |}{col 17}{res}{space 2}  .017461{col 29}{space 2} .0201974{col 40}{space 1}    0.86{col 49}{space 3}0.387{col 57}{space 4}-.0221251{col 70}{space 3} .0570471
{txt}{space 10}black {c |}{col 17}{res}{space 2} -.014451{col 29}{space 2} .0202012{col 40}{space 1}   -0.72{col 49}{space 3}0.474{col 57}{space 4}-.0540446{col 70}{space 3} .0251426
{txt}{space 10}south {c |}{col 17}{res}{space 2} .0095185{col 29}{space 2} .0196313{col 40}{space 1}    0.48{col 49}{space 3}0.628{col 57}{space 4}-.0289581{col 70}{space 3} .0479952
{txt}{space 9}party6 {c |}{col 17}{res}{space 2} .6193435{col 29}{space 2} .0192437{col 40}{space 1}   32.18{col 49}{space 3}0.000{col 57}{space 4} .5816266{col 70}{space 3} .6570604
{txt}{space 10}_cons {c |}{col 17}{res}{space 2}-.2864505{col 29}{space 2} .1166016{col 40}{space 1}   -2.46{col 49}{space 3}0.014{col 57}{space 4}-.5149855{col 70}{space 3}-.0579156
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
var(e.canddi~92){c |}{col 17}{res}{space 2} .6259938{col 29}{space 2} .0206177{col 57}{space 4} .5868606{col 70}{space 3} .6677365
{txt}{space 3}var(e.party9){c |}{col 17}{res}{space 2} .4250591{col 29}{space 2} .0161295{col 57}{space 4} .3945928{col 70}{space 3} .4578777
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
LR test of model vs. saturated: chi2({res:1})   = {res:     1.28}, Prob > chi2 = {res}0.2575
{txt}
{com}.         
.         
. * Candidate affect only 
. sem (canddiff92 <- cand6 canddiff62 ideostrength62 pidstrength2 ///
>         issueextremity2 interest62 knowledge2 education2 age2 income2 female ///
>         black south) ///
>         (cand9 <- cand6 canddiff62 ideostrength62 pidstrength2 ///
>         issueextremity2 interest62 knowledge2 education2 age2 income2 female ///
>         black south), standardized      
{res}{txt}(3102 observations with missing values excluded)

Endogenous variables

{p 0 11 2}Observed:{space 2}{res}canddiff92 cand9{p_end}
{txt}
Exogenous variables

{p 0 11 2}Observed:{space 2}{res}cand6 canddiff62 ideostrength62 pidstrength2 issueextremity2 interest62 knowledge2 education2 age2 income2 female black south{p_end}
{txt}
Fitting target model:

Iteration 0:{space 3}log likelihood = {res:-4889.4339}  
Iteration 1:{space 3}log likelihood = {res:-4889.4339}  

{col 1}Structural equation model{col 49}Number of obs{col 67}= {res}     1,138
{txt}{col 1}Estimation method{col 20}= {res}ml
{txt}{col 1}Log likelihood{col 20}= {res}-4889.4339

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}      OIM
{col 1}   Standardized{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}Structural     {col 17}{txt}{c |}
{space 2}{col 3}canddiff92   {col 17}{c |}
{space 10}cand6 {c |}{col 17}{res}{space 2} .1262536{col 29}{space 2} .0258774{col 40}{space 1}    4.88{col 49}{space 3}0.000{col 57}{space 4} .0755349{col 70}{space 3} .1769724
{txt}{space 5}canddiff62 {c |}{col 17}{res}{space 2} .3647166{col 29}{space 2} .0241907{col 40}{space 1}   15.08{col 49}{space 3}0.000{col 57}{space 4} .3173037{col 70}{space 3} .4121295
{txt}{space 2}ideostreng~62 {c |}{col 17}{res}{space 2} .0535758{col 29}{space 2} .0268049{col 40}{space 1}    2.00{col 49}{space 3}0.046{col 57}{space 4} .0010391{col 70}{space 3} .1061124
{txt}{space 3}pidstrength2 {c |}{col 17}{res}{space 2} .1163841{col 29}{space 2} .0261699{col 40}{space 1}    4.45{col 49}{space 3}0.000{col 57}{space 4} .0650921{col 70}{space 3} .1676762
{txt}{space 2}issueextrem~2 {c |}{col 17}{res}{space 2} .1147925{col 29}{space 2} .0248969{col 40}{space 1}    4.61{col 49}{space 3}0.000{col 57}{space 4} .0659955{col 70}{space 3} .1635895
{txt}{space 5}interest62 {c |}{col 17}{res}{space 2} .1204279{col 29}{space 2} .0248572{col 40}{space 1}    4.84{col 49}{space 3}0.000{col 57}{space 4} .0717086{col 70}{space 3} .1691471
{txt}{space 5}knowledge2 {c |}{col 17}{res}{space 2} .0685987{col 29}{space 2} .0271994{col 40}{space 1}    2.52{col 49}{space 3}0.012{col 57}{space 4} .0152888{col 70}{space 3} .1219086
{txt}{space 5}education2 {c |}{col 17}{res}{space 2} .0254121{col 29}{space 2} .0271192{col 40}{space 1}    0.94{col 49}{space 3}0.349{col 57}{space 4}-.0277405{col 70}{space 3} .0785647
{txt}{space 11}age2 {c |}{col 17}{res}{space 2}-.0127232{col 29}{space 2} .0247738{col 40}{space 1}   -0.51{col 49}{space 3}0.608{col 57}{space 4} -.061279{col 70}{space 3} .0358325
{txt}{space 8}income2 {c |}{col 17}{res}{space 2} .0791764{col 29}{space 2} .0264543{col 40}{space 1}    2.99{col 49}{space 3}0.003{col 57}{space 4} .0273269{col 70}{space 3} .1310258
{txt}{space 9}female {c |}{col 17}{res}{space 2} -.021906{col 29}{space 2} .0246836{col 40}{space 1}   -0.89{col 49}{space 3}0.375{col 57}{space 4} -.070285{col 70}{space 3}  .026473
{txt}{space 10}black {c |}{col 17}{res}{space 2} .0378589{col 29}{space 2}  .024722{col 40}{space 1}    1.53{col 49}{space 3}0.126{col 57}{space 4}-.0105954{col 70}{space 3} .0863132
{txt}{space 10}south {c |}{col 17}{res}{space 2} -.024471{col 29}{space 2} .0239433{col 40}{space 1}   -1.02{col 49}{space 3}0.307{col 57}{space 4}-.0713989{col 70}{space 3} .0224569
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .1880055{col 29}{space 2} .1451595{col 40}{space 1}    1.30{col 49}{space 3}0.195{col 57}{space 4} -.096502{col 70}{space 3}  .472513
{space 2}{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}cand9        {col 17}{c |}
{space 10}cand6 {c |}{col 17}{res}{space 2} .5710541{col 29}{space 2} .0196725{col 40}{space 1}   29.03{col 49}{space 3}0.000{col 57}{space 4} .5324968{col 70}{space 3} .6096115
{txt}{space 5}canddiff62 {c |}{col 17}{res}{space 2} .0292643{col 29}{space 2} .0242021{col 40}{space 1}    1.21{col 49}{space 3}0.227{col 57}{space 4}-.0181709{col 70}{space 3} .0766995
{txt}{space 2}ideostreng~62 {c |}{col 17}{res}{space 2} .0314198{col 29}{space 2} .0248656{col 40}{space 1}    1.26{col 49}{space 3}0.206{col 57}{space 4}-.0173159{col 70}{space 3} .0801556
{txt}{space 3}pidstrength2 {c |}{col 17}{res}{space 2}  .161448{col 29}{space 2} .0241016{col 40}{space 1}    6.70{col 49}{space 3}0.000{col 57}{space 4} .1142099{col 70}{space 3} .2086862
{txt}{space 2}issueextrem~2 {c |}{col 17}{res}{space 2} .0637539{col 29}{space 2} .0231989{col 40}{space 1}    2.75{col 49}{space 3}0.006{col 57}{space 4} .0182849{col 70}{space 3} .1092229
{txt}{space 5}interest62 {c |}{col 17}{res}{space 2} .0415902{col 29}{space 2} .0232109{col 40}{space 1}    1.79{col 49}{space 3}0.073{col 57}{space 4}-.0039023{col 70}{space 3} .0870828
{txt}{space 5}knowledge2 {c |}{col 17}{res}{space 2}-.0125446{col 29}{space 2} .0252638{col 40}{space 1}   -0.50{col 49}{space 3}0.620{col 57}{space 4}-.0620607{col 70}{space 3} .0369715
{txt}{space 5}education2 {c |}{col 17}{res}{space 2}-.0428978{col 29}{space 2} .0251185{col 40}{space 1}   -1.71{col 49}{space 3}0.088{col 57}{space 4}-.0921291{col 70}{space 3} .0063335
{txt}{space 11}age2 {c |}{col 17}{res}{space 2}-.0185397{col 29}{space 2} .0229567{col 40}{space 1}   -0.81{col 49}{space 3}0.419{col 57}{space 4} -.063534{col 70}{space 3} .0264547
{txt}{space 8}income2 {c |}{col 17}{res}{space 2} .0197374{col 29}{space 2} .0245919{col 40}{space 1}    0.80{col 49}{space 3}0.422{col 57}{space 4}-.0284619{col 70}{space 3} .0679366
{txt}{space 9}female {c |}{col 17}{res}{space 2} .0131282{col 29}{space 2} .0228798{col 40}{space 1}    0.57{col 49}{space 3}0.566{col 57}{space 4}-.0317154{col 70}{space 3} .0579717
{txt}{space 10}black {c |}{col 17}{res}{space 2} .0026919{col 29}{space 2} .0229307{col 40}{space 1}    0.12{col 49}{space 3}0.907{col 57}{space 4}-.0422514{col 70}{space 3} .0476351
{txt}{space 10}south {c |}{col 17}{res}{space 2} .0150108{col 29}{space 2} .0221948{col 40}{space 1}    0.68{col 49}{space 3}0.499{col 57}{space 4}-.0284902{col 70}{space 3} .0585118
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .0208744{col 29}{space 2} .1331137{col 40}{space 1}    0.16{col 49}{space 3}0.875{col 57}{space 4}-.2400237{col 70}{space 3} .2817726
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
var(e.canddi~92){c |}{col 17}{res}{space 2} .6330241{col 29}{space 2} .0205437{col 57}{space 4}  .594013{col 70}{space 3} .6745972
{txt}{space 4}var(e.cand9){c |}{col 17}{res}{space 2} .5436802{col 29}{space 2} .0191294{col 57}{space 4} .5074509{col 70}{space 3} .5824961
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
LR test of model vs. saturated: chi2({res:1})   = {res:    38.93}, Prob > chi2 = {res}0.0000
{txt}
{com}.         
.         
. * Disagregating perceived polarization scales (all but ideo and script) 
. sem (ideo9 <- affect62 ideo6 ideostrength62 pidstrength2 ///
>         issueextremity2 interest62 knowledge2 education2 age2 income2 female ///
>         black south) ///
>         (affect92 <- affect62 ideo6 ideostrength62 pidstrength2 ///
>         issueextremity2 interest62 knowledge2 education2 age2 income2 female ///
>         black south), standardized 
{res}{txt}(3120 observations with missing values excluded)

Endogenous variables

{p 0 11 2}Observed:{space 2}{res}ideo9 affect92{p_end}
{txt}
Exogenous variables

{p 0 11 2}Observed:{space 2}{res}affect62 ideo6 ideostrength62 pidstrength2 issueextremity2 interest62 knowledge2 education2 age2 income2 female black south{p_end}
{txt}
Fitting target model:

Iteration 0:{space 3}log likelihood = {res:-5135.1036}  
Iteration 1:{space 3}log likelihood = {res:-5135.1036}  

{col 1}Structural equation model{col 49}Number of obs{col 67}= {res}     1,120
{txt}{col 1}Estimation method{col 20}= {res}ml
{txt}{col 1}Log likelihood{col 20}= {res}-5135.1036

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}      OIM
{col 1}   Standardized{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}Structural     {col 17}{txt}{c |}
{space 2}{col 3}ideo9        {col 17}{c |}
{space 7}affect62 {c |}{col 17}{res}{space 2} -.002745{col 29}{space 2} .0293452{col 40}{space 1}   -0.09{col 49}{space 3}0.925{col 57}{space 4}-.0602606{col 70}{space 3} .0547706
{txt}{space 10}ideo6 {c |}{col 17}{res}{space 2} .4243503{col 29}{space 2}  .024044{col 40}{space 1}   17.65{col 49}{space 3}0.000{col 57}{space 4} .3772248{col 70}{space 3} .4714757
{txt}{space 2}ideostreng~62 {c |}{col 17}{res}{space 2} .1388307{col 29}{space 2} .0281481{col 40}{space 1}    4.93{col 49}{space 3}0.000{col 57}{space 4} .0836614{col 70}{space 3} .1939999
{txt}{space 3}pidstrength2 {c |}{col 17}{res}{space 2} .0940836{col 29}{space 2} .0284377{col 40}{space 1}    3.31{col 49}{space 3}0.001{col 57}{space 4} .0383467{col 70}{space 3} .1498204
{txt}{space 2}issueextrem~2 {c |}{col 17}{res}{space 2} -.001223{col 29}{space 2} .0260692{col 40}{space 1}   -0.05{col 49}{space 3}0.963{col 57}{space 4}-.0523177{col 70}{space 3} .0498716
{txt}{space 5}interest62 {c |}{col 17}{res}{space 2} .0760251{col 29}{space 2} .0259052{col 40}{space 1}    2.93{col 49}{space 3}0.003{col 57}{space 4} .0252518{col 70}{space 3} .1267984
{txt}{space 5}knowledge2 {c |}{col 17}{res}{space 2} .0519926{col 29}{space 2} .0282204{col 40}{space 1}    1.84{col 49}{space 3}0.065{col 57}{space 4}-.0033183{col 70}{space 3} .1073035
{txt}{space 5}education2 {c |}{col 17}{res}{space 2}   .02477{col 29}{space 2} .0284725{col 40}{space 1}    0.87{col 49}{space 3}0.384{col 57}{space 4}-.0310351{col 70}{space 3}  .080575
{txt}{space 11}age2 {c |}{col 17}{res}{space 2} .0141066{col 29}{space 2} .0256969{col 40}{space 1}    0.55{col 49}{space 3}0.583{col 57}{space 4}-.0362585{col 70}{space 3} .0644717
{txt}{space 8}income2 {c |}{col 17}{res}{space 2} .0459223{col 29}{space 2}  .027603{col 40}{space 1}    1.66{col 49}{space 3}0.096{col 57}{space 4}-.0081786{col 70}{space 3} .1000231
{txt}{space 9}female {c |}{col 17}{res}{space 2}-.0500771{col 29}{space 2} .0256738{col 40}{space 1}   -1.95{col 49}{space 3}0.051{col 57}{space 4}-.1003968{col 70}{space 3} .0002426
{txt}{space 10}black {c |}{col 17}{res}{space 2}-.0060161{col 29}{space 2} .0258755{col 40}{space 1}   -0.23{col 49}{space 3}0.816{col 57}{space 4}-.0567312{col 70}{space 3} .0446989
{txt}{space 10}south {c |}{col 17}{res}{space 2} .0448007{col 29}{space 2} .0248895{col 40}{space 1}    1.80{col 49}{space 3}0.072{col 57}{space 4}-.0039818{col 70}{space 3} .0935833
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .4126675{col 29}{space 2} .1554291{col 40}{space 1}    2.66{col 49}{space 3}0.008{col 57}{space 4}  .108032{col 70}{space 3} .7173029
{space 2}{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}affect92     {col 17}{c |}
{space 7}affect62 {c |}{col 17}{res}{space 2} .6792525{col 29}{space 2} .0173176{col 40}{space 1}   39.22{col 49}{space 3}0.000{col 57}{space 4} .6453106{col 70}{space 3} .7131944
{txt}{space 10}ideo6 {c |}{col 17}{res}{space 2}-.0200958{col 29}{space 2} .0202327{col 40}{space 1}   -0.99{col 49}{space 3}0.321{col 57}{space 4}-.0597512{col 70}{space 3} .0195597
{txt}{space 2}ideostreng~62 {c |}{col 17}{res}{space 2} .0307266{col 29}{space 2}  .021377{col 40}{space 1}    1.44{col 49}{space 3}0.151{col 57}{space 4}-.0111715{col 70}{space 3} .0726248
{txt}{space 3}pidstrength2 {c |}{col 17}{res}{space 2} .1570032{col 29}{space 2} .0212568{col 40}{space 1}    7.39{col 49}{space 3}0.000{col 57}{space 4} .1153405{col 70}{space 3} .1986658
{txt}{space 2}issueextrem~2 {c |}{col 17}{res}{space 2} .0627612{col 29}{space 2} .0195741{col 40}{space 1}    3.21{col 49}{space 3}0.001{col 57}{space 4} .0243966{col 70}{space 3} .1011258
{txt}{space 5}interest62 {c |}{col 17}{res}{space 2} .0341414{col 29}{space 2} .0195471{col 40}{space 1}    1.75{col 49}{space 3}0.081{col 57}{space 4}-.0041702{col 70}{space 3}  .072453
{txt}{space 5}knowledge2 {c |}{col 17}{res}{space 2} -.000537{col 29}{space 2} .0212626{col 40}{space 1}   -0.03{col 49}{space 3}0.980{col 57}{space 4}-.0422109{col 70}{space 3}  .041137
{txt}{space 5}education2 {c |}{col 17}{res}{space 2}-.0105879{col 29}{space 2} .0214287{col 40}{space 1}   -0.49{col 49}{space 3}0.621{col 57}{space 4}-.0525875{col 70}{space 3} .0314116
{txt}{space 11}age2 {c |}{col 17}{res}{space 2}-.0132145{col 29}{space 2} .0193354{col 40}{space 1}   -0.68{col 49}{space 3}0.494{col 57}{space 4}-.0511112{col 70}{space 3} .0246822
{txt}{space 8}income2 {c |}{col 17}{res}{space 2} .0243834{col 29}{space 2} .0207864{col 40}{space 1}    1.17{col 49}{space 3}0.241{col 57}{space 4}-.0163572{col 70}{space 3} .0651239
{txt}{space 9}female {c |}{col 17}{res}{space 2} .0134689{col 29}{space 2} .0193452{col 40}{space 1}    0.70{col 49}{space 3}0.486{col 57}{space 4} -.024447{col 70}{space 3} .0513847
{txt}{space 10}black {c |}{col 17}{res}{space 2}-.0180795{col 29}{space 2} .0194663{col 40}{space 1}   -0.93{col 49}{space 3}0.353{col 57}{space 4}-.0562326{col 70}{space 3} .0200737
{txt}{space 10}south {c |}{col 17}{res}{space 2} .0126919{col 29}{space 2} .0187501{col 40}{space 1}    0.68{col 49}{space 3}0.498{col 57}{space 4}-.0240576{col 70}{space 3} .0494414
{txt}{space 10}_cons {c |}{col 17}{res}{space 2}-.1784022{col 29}{space 2} .1139231{col 40}{space 1}   -1.57{col 49}{space 3}0.117{col 57}{space 4}-.4016874{col 70}{space 3} .0448831
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}var(e.ideo9){c |}{col 17}{res}{space 2} .6753874{col 29}{space 2} .0210474{col 57}{space 4} .6353698{col 70}{space 3} .7179255
{txt}{space 1}var(e.affect92){c |}{col 17}{res}{space 2}  .382361{col 29}{space 2} .0149299{col 57}{space 4} .3541906{col 70}{space 3}  .412772
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
LR test of model vs. saturated: chi2({res:1})   = {res:    10.95}, Prob > chi2 = {res}0.0009
{txt}
{com}.         
. sem (tax9 <- affect62 tax6 ideostrength62 pidstrength2 ///
>         issueextremity2 interest62 knowledge2 education2 age2 income2 female ///
>         black south) ///
>         (affect92 <- affect62 tax6 ideostrength62 pidstrength2 ///
>         issueextremity2 interest62 knowledge2 education2 age2 income2 female ///
>         black south), standardized 
{res}{txt}(3356 observations with missing values excluded)

Endogenous variables

{p 0 11 2}Observed:{space 2}{res}tax9 affect92{p_end}
{txt}
Exogenous variables

{p 0 11 2}Observed:{space 2}{res}affect62 tax6 ideostrength62 pidstrength2 issueextremity2 interest62 knowledge2 education2 age2 income2 female black south{p_end}
{txt}
Fitting target model:

Iteration 0:{space 3}log likelihood = {res:-4510.8387}  
Iteration 1:{space 3}log likelihood = {res:-4510.8387}  

{col 1}Structural equation model{col 49}Number of obs{col 67}= {res}       884
{txt}{col 1}Estimation method{col 20}= {res}ml
{txt}{col 1}Log likelihood{col 20}= {res}-4510.8387

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}      OIM
{col 1}   Standardized{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}Structural     {col 17}{txt}{c |}
{space 2}{col 3}tax9         {col 17}{c |}
{space 7}affect62 {c |}{col 17}{res}{space 2} .0690435{col 29}{space 2} .0323131{col 40}{space 1}    2.14{col 49}{space 3}0.033{col 57}{space 4} .0057109{col 70}{space 3}  .132376
{txt}{space 11}tax6 {c |}{col 17}{res}{space 2} .4164829{col 29}{space 2} .0269689{col 40}{space 1}   15.44{col 49}{space 3}0.000{col 57}{space 4} .3636248{col 70}{space 3}  .469341
{txt}{space 2}ideostreng~62 {c |}{col 17}{res}{space 2} .0500684{col 29}{space 2} .0314826{col 40}{space 1}    1.59{col 49}{space 3}0.112{col 57}{space 4}-.0116364{col 70}{space 3} .1117731
{txt}{space 3}pidstrength2 {c |}{col 17}{res}{space 2} .0395335{col 29}{space 2} .0320716{col 40}{space 1}    1.23{col 49}{space 3}0.218{col 57}{space 4}-.0233257{col 70}{space 3} .1023928
{txt}{space 2}issueextrem~2 {c |}{col 17}{res}{space 2} .0179958{col 29}{space 2} .0293901{col 40}{space 1}    0.61{col 49}{space 3}0.540{col 57}{space 4}-.0396078{col 70}{space 3} .0755993
{txt}{space 5}interest62 {c |}{col 17}{res}{space 2} .0498508{col 29}{space 2} .0294194{col 40}{space 1}    1.69{col 49}{space 3}0.090{col 57}{space 4}-.0078103{col 70}{space 3} .1075118
{txt}{space 5}knowledge2 {c |}{col 17}{res}{space 2} .1199111{col 29}{space 2} .0316492{col 40}{space 1}    3.79{col 49}{space 3}0.000{col 57}{space 4} .0578798{col 70}{space 3} .1819424
{txt}{space 5}education2 {c |}{col 17}{res}{space 2} .0185282{col 29}{space 2} .0317477{col 40}{space 1}    0.58{col 49}{space 3}0.559{col 57}{space 4}-.0436961{col 70}{space 3} .0807525
{txt}{space 11}age2 {c |}{col 17}{res}{space 2} .0374649{col 29}{space 2} .0289459{col 40}{space 1}    1.29{col 49}{space 3}0.196{col 57}{space 4} -.019268{col 70}{space 3} .0941979
{txt}{space 8}income2 {c |}{col 17}{res}{space 2} .0946491{col 29}{space 2} .0308321{col 40}{space 1}    3.07{col 49}{space 3}0.002{col 57}{space 4} .0342193{col 70}{space 3} .1550789
{txt}{space 9}female {c |}{col 17}{res}{space 2}-.0652661{col 29}{space 2} .0285082{col 40}{space 1}   -2.29{col 49}{space 3}0.022{col 57}{space 4}-.1211411{col 70}{space 3}-.0093911
{txt}{space 10}black {c |}{col 17}{res}{space 2} .0367108{col 29}{space 2} .0290004{col 40}{space 1}    1.27{col 49}{space 3}0.206{col 57}{space 4}-.0201289{col 70}{space 3} .0935505
{txt}{space 10}south {c |}{col 17}{res}{space 2} -.061112{col 29}{space 2} .0278944{col 40}{space 1}   -2.19{col 49}{space 3}0.028{col 57}{space 4} -.115784{col 70}{space 3}-.0064401
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .0330545{col 29}{space 2} .1678928{col 40}{space 1}    0.20{col 49}{space 3}0.844{col 57}{space 4}-.2960094{col 70}{space 3} .3621183
{space 2}{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}affect92     {col 17}{c |}
{space 7}affect62 {c |}{col 17}{res}{space 2} .6511465{col 29}{space 2} .0197266{col 40}{space 1}   33.01{col 49}{space 3}0.000{col 57}{space 4} .6124832{col 70}{space 3} .6898099
{txt}{space 11}tax6 {c |}{col 17}{res}{space 2} .0321861{col 29}{space 2} .0229471{col 40}{space 1}    1.40{col 49}{space 3}0.161{col 57}{space 4}-.0127894{col 70}{space 3} .0771616
{txt}{space 2}ideostreng~62 {c |}{col 17}{res}{space 2} .0518417{col 29}{space 2} .0240657{col 40}{space 1}    2.15{col 49}{space 3}0.031{col 57}{space 4} .0046737{col 70}{space 3} .0990097
{txt}{space 3}pidstrength2 {c |}{col 17}{res}{space 2} .1613674{col 29}{space 2} .0242519{col 40}{space 1}    6.65{col 49}{space 3}0.000{col 57}{space 4} .1138345{col 70}{space 3} .2089002
{txt}{space 2}issueextrem~2 {c |}{col 17}{res}{space 2} .0561236{col 29}{space 2} .0224323{col 40}{space 1}    2.50{col 49}{space 3}0.012{col 57}{space 4} .0121571{col 70}{space 3} .1000901
{txt}{space 5}interest62 {c |}{col 17}{res}{space 2} .0284991{col 29}{space 2} .0225105{col 40}{space 1}    1.27{col 49}{space 3}0.206{col 57}{space 4}-.0156207{col 70}{space 3} .0726188
{txt}{space 5}knowledge2 {c |}{col 17}{res}{space 2} .0064807{col 29}{space 2} .0243658{col 40}{space 1}    0.27{col 49}{space 3}0.790{col 57}{space 4}-.0412755{col 70}{space 3} .0542369
{txt}{space 5}education2 {c |}{col 17}{res}{space 2}-.0369129{col 29}{space 2} .0242565{col 40}{space 1}   -1.52{col 49}{space 3}0.128{col 57}{space 4}-.0844548{col 70}{space 3} .0106289
{txt}{space 11}age2 {c |}{col 17}{res}{space 2} -.011676{col 29}{space 2} .0221426{col 40}{space 1}   -0.53{col 49}{space 3}0.598{col 57}{space 4}-.0550747{col 70}{space 3} .0317227
{txt}{space 8}income2 {c |}{col 17}{res}{space 2} .0244015{col 29}{space 2} .0236723{col 40}{space 1}    1.03{col 49}{space 3}0.303{col 57}{space 4}-.0219954{col 70}{space 3} .0707985
{txt}{space 9}female {c |}{col 17}{res}{space 2} .0339115{col 29}{space 2} .0218346{col 40}{space 1}    1.55{col 49}{space 3}0.120{col 57}{space 4}-.0088834{col 70}{space 3} .0767065
{txt}{space 10}black {c |}{col 17}{res}{space 2}-.0113532{col 29}{space 2} .0221836{col 40}{space 1}   -0.51{col 49}{space 3}0.609{col 57}{space 4}-.0548321{col 70}{space 3} .0321258
{txt}{space 10}south {c |}{col 17}{res}{space 2}  .010664{col 29}{space 2} .0213719{col 40}{space 1}    0.50{col 49}{space 3}0.618{col 57}{space 4}-.0312242{col 70}{space 3} .0525521
{txt}{space 10}_cons {c |}{col 17}{res}{space 2}-.2242038{col 29}{space 2} .1269269{col 40}{space 1}   -1.77{col 49}{space 3}0.077{col 57}{space 4}-.4729759{col 70}{space 3} .0245683
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}var(e.tax9){c |}{col 17}{res}{space 2} .6680076{col 29}{space 2} .0236447{col 57}{space 4} .6232358{col 70}{space 3} .7159956
{txt}{space 1}var(e.affect92){c |}{col 17}{res}{space 2}  .390297{col 29}{space 2} .0170922{col 57}{space 4} .3581944{col 70}{space 3} .4252767
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
LR test of model vs. saturated: chi2({res:1})   = {res:     2.57}, Prob > chi2 = {res}0.1086
{txt}
{com}.         
. sem (health9 <- affect62 health6 ideostrength62 pidstrength2 ///
>         issueextremity2 interest62 knowledge2 education2 age2 income2 female ///
>         black south) ///
>         (affect92 <- affect62 health6 ideostrength62 pidstrength2 ///
>         issueextremity2 interest62 knowledge2 education2 age2 income2 female ///
>         black south), standardized 
{res}{txt}(3358 observations with missing values excluded)

Endogenous variables

{p 0 11 2}Observed:{space 2}{res}health9 affect92{p_end}
{txt}
Exogenous variables

{p 0 11 2}Observed:{space 2}{res}affect62 health6 ideostrength62 pidstrength2 issueextremity2 interest62 knowledge2 education2 age2 income2 female black south{p_end}
{txt}
Fitting target model:

Iteration 0:{space 3}log likelihood = {res:-4418.0428}  
Iteration 1:{space 3}log likelihood = {res:-4418.0428}  

{col 1}Structural equation model{col 49}Number of obs{col 67}= {res}       882
{txt}{col 1}Estimation method{col 20}= {res}ml
{txt}{col 1}Log likelihood{col 20}= {res}-4418.0428

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}      OIM
{col 1}   Standardized{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}Structural     {col 17}{txt}{c |}
{space 2}{col 3}health9      {col 17}{c |}
{space 7}affect62 {c |}{col 17}{res}{space 2} .0826045{col 29}{space 2} .0342931{col 40}{space 1}    2.41{col 49}{space 3}0.016{col 57}{space 4} .0153913{col 70}{space 3} .1498177
{txt}{space 8}health6 {c |}{col 17}{res}{space 2} .3979835{col 29}{space 2} .0279498{col 40}{space 1}   14.24{col 49}{space 3}0.000{col 57}{space 4} .3432028{col 70}{space 3} .4527641
{txt}{space 2}ideostreng~62 {c |}{col 17}{res}{space 2} .0375695{col 29}{space 2}  .033364{col 40}{space 1}    1.13{col 49}{space 3}0.260{col 57}{space 4}-.0278228{col 70}{space 3} .1029617
{txt}{space 3}pidstrength2 {c |}{col 17}{res}{space 2} .0620557{col 29}{space 2} .0336472{col 40}{space 1}    1.84{col 49}{space 3}0.065{col 57}{space 4}-.0038917{col 70}{space 3}  .128003
{txt}{space 2}issueextrem~2 {c |}{col 17}{res}{space 2} .0478236{col 29}{space 2}  .030965{col 40}{space 1}    1.54{col 49}{space 3}0.122{col 57}{space 4}-.0128667{col 70}{space 3} .1085138
{txt}{space 5}interest62 {c |}{col 17}{res}{space 2} .0579993{col 29}{space 2}  .030886{col 40}{space 1}    1.88{col 49}{space 3}0.060{col 57}{space 4}-.0025363{col 70}{space 3} .1185348
{txt}{space 5}knowledge2 {c |}{col 17}{res}{space 2} .0134862{col 29}{space 2} .0334318{col 40}{space 1}    0.40{col 49}{space 3}0.687{col 57}{space 4} -.052039{col 70}{space 3} .0790114
{txt}{space 5}education2 {c |}{col 17}{res}{space 2} .0116384{col 29}{space 2}  .033492{col 40}{space 1}    0.35{col 49}{space 3}0.728{col 57}{space 4}-.0540046{col 70}{space 3} .0772815
{txt}{space 11}age2 {c |}{col 17}{res}{space 2} .0166941{col 29}{space 2} .0304923{col 40}{space 1}    0.55{col 49}{space 3}0.584{col 57}{space 4}-.0430696{col 70}{space 3} .0764578
{txt}{space 8}income2 {c |}{col 17}{res}{space 2} .0833432{col 29}{space 2} .0325417{col 40}{space 1}    2.56{col 49}{space 3}0.010{col 57}{space 4} .0195626{col 70}{space 3} .1471238
{txt}{space 9}female {c |}{col 17}{res}{space 2}-.0143277{col 29}{space 2} .0299717{col 40}{space 1}   -0.48{col 49}{space 3}0.633{col 57}{space 4}-.0730712{col 70}{space 3} .0444157
{txt}{space 10}black {c |}{col 17}{res}{space 2} .0151037{col 29}{space 2} .0305391{col 40}{space 1}    0.49{col 49}{space 3}0.621{col 57}{space 4}-.0447518{col 70}{space 3} .0749591
{txt}{space 10}south {c |}{col 17}{res}{space 2}-.0077859{col 29}{space 2} .0294739{col 40}{space 1}   -0.26{col 49}{space 3}0.792{col 57}{space 4}-.0655538{col 70}{space 3}  .049982
{txt}{space 10}_cons {c |}{col 17}{res}{space 2}-.0481999{col 29}{space 2} .1760846{col 40}{space 1}   -0.27{col 49}{space 3}0.784{col 57}{space 4}-.3933194{col 70}{space 3} .2969197
{space 2}{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}affect92     {col 17}{c |}
{space 7}affect62 {c |}{col 17}{res}{space 2} .6532282{col 29}{space 2} .0199853{col 40}{space 1}   32.69{col 49}{space 3}0.000{col 57}{space 4} .6140578{col 70}{space 3} .6923986
{txt}{space 8}health6 {c |}{col 17}{res}{space 2} .0062259{col 29}{space 2} .0225759{col 40}{space 1}    0.28{col 49}{space 3}0.783{col 57}{space 4}-.0380221{col 70}{space 3} .0504739
{txt}{space 2}ideostreng~62 {c |}{col 17}{res}{space 2} .0491102{col 29}{space 2} .0242568{col 40}{space 1}    2.02{col 49}{space 3}0.043{col 57}{space 4} .0015679{col 70}{space 3} .0966526
{txt}{space 3}pidstrength2 {c |}{col 17}{res}{space 2} .1644218{col 29}{space 2} .0242245{col 40}{space 1}    6.79{col 49}{space 3}0.000{col 57}{space 4} .1169426{col 70}{space 3}  .211901
{txt}{space 2}issueextrem~2 {c |}{col 17}{res}{space 2} .0592226{col 29}{space 2} .0225102{col 40}{space 1}    2.63{col 49}{space 3}0.009{col 57}{space 4} .0151034{col 70}{space 3} .1033418
{txt}{space 5}interest62 {c |}{col 17}{res}{space 2}  .030908{col 29}{space 2} .0224975{col 40}{space 1}    1.37{col 49}{space 3}0.169{col 57}{space 4}-.0131864{col 70}{space 3} .0750023
{txt}{space 5}knowledge2 {c |}{col 17}{res}{space 2} .0103256{col 29}{space 2} .0243159{col 40}{space 1}    0.42{col 49}{space 3}0.671{col 57}{space 4}-.0373327{col 70}{space 3} .0579839
{txt}{space 5}education2 {c |}{col 17}{res}{space 2}-.0316563{col 29}{space 2} .0243493{col 40}{space 1}   -1.30{col 49}{space 3}0.194{col 57}{space 4}  -.07938{col 70}{space 3} .0160674
{txt}{space 11}age2 {c |}{col 17}{res}{space 2}-.0102293{col 29}{space 2} .0221794{col 40}{space 1}   -0.46{col 49}{space 3}0.645{col 57}{space 4}-.0537001{col 70}{space 3} .0332416
{txt}{space 8}income2 {c |}{col 17}{res}{space 2} .0224258{col 29}{space 2}  .023751{col 40}{space 1}    0.94{col 49}{space 3}0.345{col 57}{space 4}-.0241253{col 70}{space 3}  .068977
{txt}{space 9}female {c |}{col 17}{res}{space 2} .0321838{col 29}{space 2} .0217885{col 40}{space 1}    1.48{col 49}{space 3}0.140{col 57}{space 4}-.0105208{col 70}{space 3} .0748885
{txt}{space 10}black {c |}{col 17}{res}{space 2}-.0099658{col 29}{space 2} .0222128{col 40}{space 1}   -0.45{col 49}{space 3}0.654{col 57}{space 4}-.0535021{col 70}{space 3} .0335706
{txt}{space 10}south {c |}{col 17}{res}{space 2} .0105062{col 29}{space 2} .0214357{col 40}{space 1}    0.49{col 49}{space 3}0.624{col 57}{space 4} -.031507{col 70}{space 3} .0525195
{txt}{space 10}_cons {c |}{col 17}{res}{space 2}-.2196119{col 29}{space 2} .1270893{col 40}{space 1}   -1.73{col 49}{space 3}0.084{col 57}{space 4}-.4687023{col 70}{space 3} .0294785
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}var(e.health9){c |}{col 17}{res}{space 2} .7410498{col 29}{space 2} .0236942{col 57}{space 4} .6960353{col 70}{space 3} .7889756
{txt}{space 1}var(e.affect92){c |}{col 17}{res}{space 2} .3919836{col 29}{space 2} .0171721{col 57}{space 4} .3597313{col 70}{space 3} .4271274
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
LR test of model vs. saturated: chi2({res:1})   = {res:    12.96}, Prob > chi2 = {res}0.0003
{txt}
{com}.         
. sem (immigrants9 <- affect62 immigrants6 ideostrength62 pidstrength2 ///
>         issueextremity2 interest62 knowledge2 education2 age2 income2 female ///
>         black south) ///
>         (affect92 <- affect62 immigrants6 ideostrength62 pidstrength2 ///
>         issueextremity2 interest62 knowledge2 education2 age2 income2 female ///
>         black south), standardized 
{res}{txt}(3361 observations with missing values excluded)

Endogenous variables

{p 0 11 2}Observed:{space 2}{res}immigrants9 affect92{p_end}
{txt}
Exogenous variables

{p 0 11 2}Observed:{space 2}{res}affect62 immigrants6 ideostrength62 pidstrength2 issueextremity2 interest62 knowledge2 education2 age2 income2 female black south{p_end}
{txt}
Fitting target model:

Iteration 0:{space 3}log likelihood = {res:-4317.5972}  
Iteration 1:{space 3}log likelihood = {res:-4317.5972}  

{col 1}Structural equation model{col 49}Number of obs{col 67}= {res}       879
{txt}{col 1}Estimation method{col 20}= {res}ml
{txt}{col 1}Log likelihood{col 20}= {res}-4317.5972

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}      OIM
{col 1}   Standardized{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}Structural     {col 17}{txt}{c |}
{space 2}{col 3}immigrants9  {col 17}{c |}
{space 7}affect62 {c |}{col 17}{res}{space 2} .1276959{col 29}{space 2} .0365732{col 40}{space 1}    3.49{col 49}{space 3}0.000{col 57}{space 4} .0560138{col 70}{space 3}  .199378
{txt}{space 4}immigrants6 {c |}{col 17}{res}{space 2} .2503464{col 29}{space 2} .0305053{col 40}{space 1}    8.21{col 49}{space 3}0.000{col 57}{space 4} .1905571{col 70}{space 3} .3101358
{txt}{space 2}ideostreng~62 {c |}{col 17}{res}{space 2} .0539161{col 29}{space 2} .0359233{col 40}{space 1}    1.50{col 49}{space 3}0.133{col 57}{space 4}-.0164923{col 70}{space 3} .1243244
{txt}{space 3}pidstrength2 {c |}{col 17}{res}{space 2}-.0263279{col 29}{space 2} .0364468{col 40}{space 1}   -0.72{col 49}{space 3}0.470{col 57}{space 4}-.0977622{col 70}{space 3} .0451065
{txt}{space 2}issueextrem~2 {c |}{col 17}{res}{space 2} .0952298{col 29}{space 2} .0334275{col 40}{space 1}    2.85{col 49}{space 3}0.004{col 57}{space 4} .0297131{col 70}{space 3} .1607464
{txt}{space 5}interest62 {c |}{col 17}{res}{space 2} .0645947{col 29}{space 2} .0333673{col 40}{space 1}    1.94{col 49}{space 3}0.053{col 57}{space 4} -.000804{col 70}{space 3} .1299933
{txt}{space 5}knowledge2 {c |}{col 17}{res}{space 2}-.0651265{col 29}{space 2} .0358642{col 40}{space 1}   -1.82{col 49}{space 3}0.069{col 57}{space 4} -.135419{col 70}{space 3} .0051661
{txt}{space 5}education2 {c |}{col 17}{res}{space 2} .0108482{col 29}{space 2} .0362539{col 40}{space 1}    0.30{col 49}{space 3}0.765{col 57}{space 4}-.0602082{col 70}{space 3} .0819045
{txt}{space 11}age2 {c |}{col 17}{res}{space 2}-.0769588{col 29}{space 2} .0328386{col 40}{space 1}   -2.34{col 49}{space 3}0.019{col 57}{space 4}-.1413212{col 70}{space 3}-.0125963
{txt}{space 8}income2 {c |}{col 17}{res}{space 2} .0521736{col 29}{space 2} .0352531{col 40}{space 1}    1.48{col 49}{space 3}0.139{col 57}{space 4}-.0169212{col 70}{space 3} .1212684
{txt}{space 9}female {c |}{col 17}{res}{space 2} .0501711{col 29}{space 2} .0323651{col 40}{space 1}    1.55{col 49}{space 3}0.121{col 57}{space 4}-.0132632{col 70}{space 3} .1136055
{txt}{space 10}black {c |}{col 17}{res}{space 2}-.0160943{col 29}{space 2} .0330366{col 40}{space 1}   -0.49{col 49}{space 3}0.626{col 57}{space 4}-.0808447{col 70}{space 3} .0486562
{txt}{space 10}south {c |}{col 17}{res}{space 2}-.0007003{col 29}{space 2} .0318711{col 40}{space 1}   -0.02{col 49}{space 3}0.982{col 57}{space 4}-.0631664{col 70}{space 3} .0617659
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .2863455{col 29}{space 2} .1926371{col 40}{space 1}    1.49{col 49}{space 3}0.137{col 57}{space 4}-.0912162{col 70}{space 3} .6639072
{space 2}{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}affect92     {col 17}{c |}
{space 7}affect62 {c |}{col 17}{res}{space 2} .6541519{col 29}{space 2} .0197791{col 40}{space 1}   33.07{col 49}{space 3}0.000{col 57}{space 4} .6153855{col 70}{space 3} .6929182
{txt}{space 4}immigrants6 {c |}{col 17}{res}{space 2}-.0149899{col 29}{space 2} .0215595{col 40}{space 1}   -0.70{col 49}{space 3}0.487{col 57}{space 4}-.0572458{col 70}{space 3} .0272659
{txt}{space 2}ideostreng~62 {c |}{col 17}{res}{space 2} .0494931{col 29}{space 2} .0242796{col 40}{space 1}    2.04{col 49}{space 3}0.042{col 57}{space 4}  .001906{col 70}{space 3} .0970802
{txt}{space 3}pidstrength2 {c |}{col 17}{res}{space 2} .1664043{col 29}{space 2} .0243273{col 40}{space 1}    6.84{col 49}{space 3}0.000{col 57}{space 4} .1187237{col 70}{space 3} .2140849
{txt}{space 2}issueextrem~2 {c |}{col 17}{res}{space 2} .0601178{col 29}{space 2}  .022668{col 40}{space 1}    2.65{col 49}{space 3}0.008{col 57}{space 4} .0156894{col 70}{space 3} .1045462
{txt}{space 5}interest62 {c |}{col 17}{res}{space 2} .0346639{col 29}{space 2} .0225866{col 40}{space 1}    1.53{col 49}{space 3}0.125{col 57}{space 4}-.0096049{col 70}{space 3} .0789328
{txt}{space 5}knowledge2 {c |}{col 17}{res}{space 2} .0070164{col 29}{space 2} .0242839{col 40}{space 1}    0.29{col 49}{space 3}0.773{col 57}{space 4}-.0405791{col 70}{space 3}  .054612
{txt}{space 5}education2 {c |}{col 17}{res}{space 2}-.0297142{col 29}{space 2} .0244834{col 40}{space 1}   -1.21{col 49}{space 3}0.225{col 57}{space 4}-.0777008{col 70}{space 3} .0182724
{txt}{space 11}age2 {c |}{col 17}{res}{space 2}-.0098856{col 29}{space 2} .0222687{col 40}{space 1}   -0.44{col 49}{space 3}0.657{col 57}{space 4}-.0535314{col 70}{space 3} .0337602
{txt}{space 8}income2 {c |}{col 17}{res}{space 2} .0238715{col 29}{space 2} .0238457{col 40}{space 1}    1.00{col 49}{space 3}0.317{col 57}{space 4}-.0228652{col 70}{space 3} .0706083
{txt}{space 9}female {c |}{col 17}{res}{space 2} .0309761{col 29}{space 2} .0218896{col 40}{space 1}    1.42{col 49}{space 3}0.157{col 57}{space 4}-.0119267{col 70}{space 3} .0738789
{txt}{space 10}black {c |}{col 17}{res}{space 2}-.0094869{col 29}{space 2} .0223207{col 40}{space 1}   -0.43{col 49}{space 3}0.671{col 57}{space 4}-.0532347{col 70}{space 3} .0342609
{txt}{space 10}south {c |}{col 17}{res}{space 2} .0085331{col 29}{space 2} .0215298{col 40}{space 1}    0.40{col 49}{space 3}0.692{col 57}{space 4}-.0336646{col 70}{space 3} .0507307
{txt}{space 10}_cons {c |}{col 17}{res}{space 2}-.2067941{col 29}{space 2} .1281487{col 40}{space 1}   -1.61{col 49}{space 3}0.107{col 57}{space 4}-.4579609{col 70}{space 3} .0443727
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
var(e.immigr~s9){c |}{col 17}{res}{space 2} .8636821{col 29}{space 2} .0207652{col 57}{space 4}  .823927{col 70}{space 3} .9053554
{txt}{space 1}var(e.affect92){c |}{col 17}{res}{space 2} .3941643{col 29}{space 2} .0172795{col 57}{space 4} .3617112{col 70}{space 3} .4295292
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
LR test of model vs. saturated: chi2({res:1})   = {res:     6.22}, Prob > chi2 = {res}0.0126
{txt}
{com}.         
. sem (gay9 <- affect62 gay6 ideostrength62 pidstrength2 ///
>         issueextremity2 interest62 knowledge2 education2 age2 income2 female ///
>         black south) ///
>         (affect92 <- affect62 gay6 ideostrength62 pidstrength2 ///
>         issueextremity2 interest62 knowledge2 education2 age2 income2 female ///
>         black south), standardized      
{res}{txt}(3358 observations with missing values excluded)

Endogenous variables

{p 0 11 2}Observed:{space 2}{res}gay9 affect92{p_end}
{txt}
Exogenous variables

{p 0 11 2}Observed:{space 2}{res}affect62 gay6 ideostrength62 pidstrength2 issueextremity2 interest62 knowledge2 education2 age2 income2 female black south{p_end}
{txt}
Fitting target model:

Iteration 0:{space 3}log likelihood = {res:-4363.8659}  
Iteration 1:{space 3}log likelihood = {res:-4363.8659}  

{col 1}Structural equation model{col 49}Number of obs{col 67}= {res}       882
{txt}{col 1}Estimation method{col 20}= {res}ml
{txt}{col 1}Log likelihood{col 20}= {res}-4363.8659

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}      OIM
{col 1}   Standardized{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}Structural     {col 17}{txt}{c |}
{space 2}{col 3}gay9         {col 17}{c |}
{space 7}affect62 {c |}{col 17}{res}{space 2} .0926886{col 29}{space 2}   .03541{col 40}{space 1}    2.62{col 49}{space 3}0.009{col 57}{space 4} .0232862{col 70}{space 3} .1620909
{txt}{space 11}gay6 {c |}{col 17}{res}{space 2} .2419087{col 29}{space 2} .0305162{col 40}{space 1}    7.93{col 49}{space 3}0.000{col 57}{space 4} .1820981{col 70}{space 3} .3017193
{txt}{space 2}ideostreng~62 {c |}{col 17}{res}{space 2} .1203814{col 29}{space 2} .0343216{col 40}{space 1}    3.51{col 49}{space 3}0.000{col 57}{space 4} .0531123{col 70}{space 3} .1876505
{txt}{space 3}pidstrength2 {c |}{col 17}{res}{space 2}  .105695{col 29}{space 2} .0347256{col 40}{space 1}    3.04{col 49}{space 3}0.002{col 57}{space 4}  .037634{col 70}{space 3} .1737559
{txt}{space 2}issueextrem~2 {c |}{col 17}{res}{space 2} .0689758{col 29}{space 2} .0320573{col 40}{space 1}    2.15{col 49}{space 3}0.031{col 57}{space 4} .0061448{col 70}{space 3} .1318069
{txt}{space 5}interest62 {c |}{col 17}{res}{space 2} .0938198{col 29}{space 2} .0319249{col 40}{space 1}    2.94{col 49}{space 3}0.003{col 57}{space 4} .0312482{col 70}{space 3} .1563914
{txt}{space 5}knowledge2 {c |}{col 17}{res}{space 2} .0096791{col 29}{space 2} .0345145{col 40}{space 1}    0.28{col 49}{space 3}0.779{col 57}{space 4}-.0579681{col 70}{space 3} .0773264
{txt}{space 5}education2 {c |}{col 17}{res}{space 2}-.0281362{col 29}{space 2} .0346865{col 40}{space 1}   -0.81{col 49}{space 3}0.417{col 57}{space 4}-.0961206{col 70}{space 3} .0398482
{txt}{space 11}age2 {c |}{col 17}{res}{space 2} .0149928{col 29}{space 2} .0316256{col 40}{space 1}    0.47{col 49}{space 3}0.635{col 57}{space 4}-.0469922{col 70}{space 3} .0769777
{txt}{space 8}income2 {c |}{col 17}{res}{space 2} .0539087{col 29}{space 2} .0337989{col 40}{space 1}    1.59{col 49}{space 3}0.111{col 57}{space 4} -.012336{col 70}{space 3} .1201534
{txt}{space 9}female {c |}{col 17}{res}{space 2} .0019057{col 29}{space 2} .0310932{col 40}{space 1}    0.06{col 49}{space 3}0.951{col 57}{space 4}-.0590358{col 70}{space 3} .0628473
{txt}{space 10}black {c |}{col 17}{res}{space 2}-.0610369{col 29}{space 2}  .031588{col 40}{space 1}   -1.93{col 49}{space 3}0.053{col 57}{space 4}-.1229482{col 70}{space 3} .0008744
{txt}{space 10}south {c |}{col 17}{res}{space 2}-.0699931{col 29}{space 2}  .030485{col 40}{space 1}   -2.30{col 49}{space 3}0.022{col 57}{space 4}-.1297427{col 70}{space 3}-.0102436
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .0758612{col 29}{space 2} .1839414{col 40}{space 1}    0.41{col 49}{space 3}0.680{col 57}{space 4}-.2846574{col 70}{space 3} .4363797
{space 2}{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}affect92     {col 17}{c |}
{space 7}affect62 {c |}{col 17}{res}{space 2} .6498856{col 29}{space 2} .0199142{col 40}{space 1}   32.63{col 49}{space 3}0.000{col 57}{space 4} .6108545{col 70}{space 3} .6889167
{txt}{space 11}gay6 {c |}{col 17}{res}{space 2} .0264323{col 29}{space 2}  .022206{col 40}{space 1}    1.19{col 49}{space 3}0.234{col 57}{space 4}-.0170906{col 70}{space 3} .0699553
{txt}{space 2}ideostreng~62 {c |}{col 17}{res}{space 2} .0489769{col 29}{space 2} .0242069{col 40}{space 1}    2.02{col 49}{space 3}0.043{col 57}{space 4} .0015323{col 70}{space 3} .0964214
{txt}{space 3}pidstrength2 {c |}{col 17}{res}{space 2} .1634615{col 29}{space 2} .0241803{col 40}{space 1}    6.76{col 49}{space 3}0.000{col 57}{space 4} .1160689{col 70}{space 3} .2108541
{txt}{space 2}issueextrem~2 {c |}{col 17}{res}{space 2} .0571123{col 29}{space 2} .0224875{col 40}{space 1}    2.54{col 49}{space 3}0.011{col 57}{space 4} .0130377{col 70}{space 3} .1011869
{txt}{space 5}interest62 {c |}{col 17}{res}{space 2} .0300392{col 29}{space 2} .0224787{col 40}{space 1}    1.34{col 49}{space 3}0.181{col 57}{space 4}-.0140183{col 70}{space 3} .0740967
{txt}{space 5}knowledge2 {c |}{col 17}{res}{space 2} .0112768{col 29}{space 2} .0241817{col 40}{space 1}    0.47{col 49}{space 3}0.641{col 57}{space 4}-.0361185{col 70}{space 3}  .058672
{txt}{space 5}education2 {c |}{col 17}{res}{space 2}-.0359988{col 29}{space 2} .0242984{col 40}{space 1}   -1.48{col 49}{space 3}0.138{col 57}{space 4}-.0836227{col 70}{space 3} .0116251
{txt}{space 11}age2 {c |}{col 17}{res}{space 2}-.0093964{col 29}{space 2} .0221599{col 40}{space 1}   -0.42{col 49}{space 3}0.672{col 57}{space 4} -.052829{col 70}{space 3} .0340361
{txt}{space 8}income2 {c |}{col 17}{res}{space 2} .0259762{col 29}{space 2}  .023711{col 40}{space 1}    1.10{col 49}{space 3}0.273{col 57}{space 4}-.0204966{col 70}{space 3}  .072449
{txt}{space 9}female {c |}{col 17}{res}{space 2} .0308593{col 29}{space 2} .0217732{col 40}{space 1}    1.42{col 49}{space 3}0.156{col 57}{space 4}-.0118155{col 70}{space 3}  .073534
{txt}{space 10}black {c |}{col 17}{res}{space 2} -.009053{col 29}{space 2} .0221827{col 40}{space 1}   -0.41{col 49}{space 3}0.683{col 57}{space 4}-.0525303{col 70}{space 3} .0344243
{txt}{space 10}south {c |}{col 17}{res}{space 2} .0119338{col 29}{space 2}  .021428{col 40}{space 1}    0.56{col 49}{space 3}0.578{col 57}{space 4}-.0300644{col 70}{space 3}  .053932
{txt}{space 10}_cons {c |}{col 17}{res}{space 2}-.2374994{col 29}{space 2} .1272178{col 40}{space 1}   -1.87{col 49}{space 3}0.062{col 57}{space 4}-.4868417{col 70}{space 3} .0118428
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}var(e.gay9){c |}{col 17}{res}{space 2} .7978256{col 29}{space 2} .0229047{col 57}{space 4} .7541728{col 70}{space 3} .8440052
{txt}{space 1}var(e.affect92){c |}{col 17}{res}{space 2} .3916374{col 29}{space 2} .0171597{col 57}{space 4} .3594087{col 70}{space 3} .4267561
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
LR test of model vs. saturated: chi2({res:1})   = {res:     0.36}, Prob > chi2 = {res}0.5472
{txt}
{com}.         
. sem (fisa9 <- affect62 fisa6 ideostrength62 pidstrength2 ///
>         issueextremity2 interest62 knowledge2 education2 age2 income2 female ///
>         black south) ///
>         (affect92 <- affect62 fisa6 ideostrength62 pidstrength2 ///
>         issueextremity2 interest62 knowledge2 education2 age2 income2 female ///
>         black south), standardized 
{res}{txt}(3358 observations with missing values excluded)

Endogenous variables

{p 0 11 2}Observed:{space 2}{res}fisa9 affect92{p_end}
{txt}
Exogenous variables

{p 0 11 2}Observed:{space 2}{res}affect62 fisa6 ideostrength62 pidstrength2 issueextremity2 interest62 knowledge2 education2 age2 income2 female black south{p_end}
{txt}
Fitting target model:

Iteration 0:{space 3}log likelihood = {res:-4546.3928}  
Iteration 1:{space 3}log likelihood = {res:-4546.3928}  

{col 1}Structural equation model{col 49}Number of obs{col 67}= {res}       882
{txt}{col 1}Estimation method{col 20}= {res}ml
{txt}{col 1}Log likelihood{col 20}= {res}-4546.3928

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}      OIM
{col 1}   Standardized{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}Structural     {col 17}{txt}{c |}
{space 2}{col 3}fisa9        {col 17}{c |}
{space 7}affect62 {c |}{col 17}{res}{space 2} .1311138{col 29}{space 2} .0355686{col 40}{space 1}    3.69{col 49}{space 3}0.000{col 57}{space 4} .0614006{col 70}{space 3}  .200827
{txt}{space 10}fisa6 {c |}{col 17}{res}{space 2}  .277384{col 29}{space 2} .0313267{col 40}{space 1}    8.85{col 49}{space 3}0.000{col 57}{space 4} .2159848{col 70}{space 3} .3387833
{txt}{space 2}ideostreng~62 {c |}{col 17}{res}{space 2} .0465364{col 29}{space 2} .0348781{col 40}{space 1}    1.33{col 49}{space 3}0.182{col 57}{space 4}-.0218235{col 70}{space 3} .1148963
{txt}{space 3}pidstrength2 {c |}{col 17}{res}{space 2} .0173277{col 29}{space 2} .0355932{col 40}{space 1}    0.49{col 49}{space 3}0.626{col 57}{space 4}-.0524337{col 70}{space 3}  .087089
{txt}{space 2}issueextrem~2 {c |}{col 17}{res}{space 2} .0376882{col 29}{space 2}  .032645{col 40}{space 1}    1.15{col 49}{space 3}0.248{col 57}{space 4}-.0262948{col 70}{space 3} .1016711
{txt}{space 5}interest62 {c |}{col 17}{res}{space 2} .0917758{col 29}{space 2} .0324606{col 40}{space 1}    2.83{col 49}{space 3}0.005{col 57}{space 4} .0281542{col 70}{space 3} .1553974
{txt}{space 5}knowledge2 {c |}{col 17}{res}{space 2}-.0044813{col 29}{space 2} .0349153{col 40}{space 1}   -0.13{col 49}{space 3}0.898{col 57}{space 4}-.0729141{col 70}{space 3} .0639515
{txt}{space 5}education2 {c |}{col 17}{res}{space 2}-.0098427{col 29}{space 2} .0350853{col 40}{space 1}   -0.28{col 49}{space 3}0.779{col 57}{space 4}-.0786086{col 70}{space 3} .0589232
{txt}{space 11}age2 {c |}{col 17}{res}{space 2}  .102762{col 29}{space 2} .0317824{col 40}{space 1}    3.23{col 49}{space 3}0.001{col 57}{space 4} .0404697{col 70}{space 3} .1650542
{txt}{space 8}income2 {c |}{col 17}{res}{space 2} .0583197{col 29}{space 2} .0342617{col 40}{space 1}    1.70{col 49}{space 3}0.089{col 57}{space 4}-.0088319{col 70}{space 3} .1254714
{txt}{space 9}female {c |}{col 17}{res}{space 2}-.0120756{col 29}{space 2} .0314731{col 40}{space 1}   -0.38{col 49}{space 3}0.701{col 57}{space 4}-.0737618{col 70}{space 3} .0496105
{txt}{space 10}black {c |}{col 17}{res}{space 2}  .010299{col 29}{space 2} .0320245{col 40}{space 1}    0.32{col 49}{space 3}0.748{col 57}{space 4}-.0524679{col 70}{space 3} .0730659
{txt}{space 10}south {c |}{col 17}{res}{space 2}-.0205185{col 29}{space 2} .0309372{col 40}{space 1}   -0.66{col 49}{space 3}0.507{col 57}{space 4}-.0811542{col 70}{space 3} .0401172
{txt}{space 10}_cons {c |}{col 17}{res}{space 2}-.0019324{col 29}{space 2} .1855334{col 40}{space 1}   -0.01{col 49}{space 3}0.992{col 57}{space 4}-.3655711{col 70}{space 3} .3617063
{space 2}{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}affect92     {col 17}{c |}
{space 7}affect62 {c |}{col 17}{res}{space 2} .6509589{col 29}{space 2} .0198263{col 40}{space 1}   32.83{col 49}{space 3}0.000{col 57}{space 4}    .6121{col 70}{space 3} .6898179
{txt}{space 10}fisa6 {c |}{col 17}{res}{space 2} .0253513{col 29}{space 2} .0227826{col 40}{space 1}    1.11{col 49}{space 3}0.266{col 57}{space 4}-.0193018{col 70}{space 3} .0700044
{txt}{space 2}ideostreng~62 {c |}{col 17}{res}{space 2} .0497847{col 29}{space 2} .0241701{col 40}{space 1}    2.06{col 49}{space 3}0.039{col 57}{space 4} .0024123{col 70}{space 3} .0971572
{txt}{space 3}pidstrength2 {c |}{col 17}{res}{space 2} .1614705{col 29}{space 2} .0243862{col 40}{space 1}    6.62{col 49}{space 3}0.000{col 57}{space 4} .1136746{col 70}{space 3} .2092665
{txt}{space 2}issueextrem~2 {c |}{col 17}{res}{space 2} .0565846{col 29}{space 2} .0226038{col 40}{space 1}    2.50{col 49}{space 3}0.012{col 57}{space 4} .0122819{col 70}{space 3} .1008872
{txt}{space 5}interest62 {c |}{col 17}{res}{space 2}  .028992{col 29}{space 2}  .022601{col 40}{space 1}    1.28{col 49}{space 3}0.200{col 57}{space 4}-.0153052{col 70}{space 3} .0732891
{txt}{space 5}knowledge2 {c |}{col 17}{res}{space 2} .0082506{col 29}{space 2} .0241946{col 40}{space 1}    0.34{col 49}{space 3}0.733{col 57}{space 4}-.0391699{col 70}{space 3} .0556711
{txt}{space 5}education2 {c |}{col 17}{res}{space 2}-.0344931{col 29}{space 2} .0243011{col 40}{space 1}   -1.42{col 49}{space 3}0.156{col 57}{space 4}-.0821224{col 70}{space 3} .0131361
{txt}{space 11}age2 {c |}{col 17}{res}{space 2}-.0102125{col 29}{space 2} .0221723{col 40}{space 1}   -0.46{col 49}{space 3}0.645{col 57}{space 4}-.0536693{col 70}{space 3} .0332444
{txt}{space 8}income2 {c |}{col 17}{res}{space 2} .0226446{col 29}{space 2} .0237812{col 40}{space 1}    0.95{col 49}{space 3}0.341{col 57}{space 4}-.0239656{col 70}{space 3} .0692548
{txt}{space 9}female {c |}{col 17}{res}{space 2} .0328495{col 29}{space 2} .0217987{col 40}{space 1}    1.51{col 49}{space 3}0.132{col 57}{space 4}-.0098751{col 70}{space 3} .0755741
{txt}{space 10}black {c |}{col 17}{res}{space 2}-.0100269{col 29}{space 2} .0221921{col 40}{space 1}   -0.45{col 49}{space 3}0.651{col 57}{space 4}-.0535227{col 70}{space 3} .0334689
{txt}{space 10}south {c |}{col 17}{res}{space 2} .0096859{col 29}{space 2} .0214433{col 40}{space 1}    0.45{col 49}{space 3}0.651{col 57}{space 4}-.0323423{col 70}{space 3}  .051714
{txt}{space 10}_cons {c |}{col 17}{res}{space 2}-.2100287{col 29}{space 2} .1274307{col 40}{space 1}   -1.65{col 49}{space 3}0.099{col 57}{space 4}-.4597883{col 70}{space 3} .0397309
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}var(e.fisa9){c |}{col 17}{res}{space 2} .8161396{col 29}{space 2} .0224576{col 57}{space 4} .7732893{col 70}{space 3} .8613643
{txt}{space 1}var(e.affect92){c |}{col 17}{res}{space 2} .3919096{col 29}{space 2} .0171694{col 57}{space 4} .3596624{col 70}{space 3} .4270481
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
LR test of model vs. saturated: chi2({res:1})   = {res:     1.46}, Prob > chi2 = {res}0.2263
{txt}
{com}.         
. sem (terror9 <- affect62 terror6 ideostrength62 pidstrength2 ///
>         issueextremity2 interest62 knowledge2 education2 age2 income2 female ///
>         black south) ///
>         (affect92 <- affect62 terror6 ideostrength62 pidstrength2 ///
>         issueextremity2 interest62 knowledge2 education2 age2 income2 female ///
>         black south), standardized      
{res}{txt}(3357 observations with missing values excluded)

Endogenous variables

{p 0 11 2}Observed:{space 2}{res}terror9 affect92{p_end}
{txt}
Exogenous variables

{p 0 11 2}Observed:{space 2}{res}affect62 terror6 ideostrength62 pidstrength2 issueextremity2 interest62 knowledge2 education2 age2 income2 female black south{p_end}
{txt}
Fitting target model:

Iteration 0:{space 3}log likelihood = {res:-4499.8688}  
Iteration 1:{space 3}log likelihood = {res:-4499.8688}  

{col 1}Structural equation model{col 49}Number of obs{col 67}= {res}       883
{txt}{col 1}Estimation method{col 20}= {res}ml
{txt}{col 1}Log likelihood{col 20}= {res}-4499.8688

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}      OIM
{col 1}   Standardized{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}Structural     {col 17}{txt}{c |}
{space 2}{col 3}terror9      {col 17}{c |}
{space 7}affect62 {c |}{col 17}{res}{space 2} .1612522{col 29}{space 2} .0337136{col 40}{space 1}    4.78{col 49}{space 3}0.000{col 57}{space 4} .0951748{col 70}{space 3} .2273297
{txt}{space 8}terror6 {c |}{col 17}{res}{space 2} .3994155{col 29}{space 2} .0274456{col 40}{space 1}   14.55{col 49}{space 3}0.000{col 57}{space 4} .3456232{col 70}{space 3} .4532078
{txt}{space 2}ideostreng~62 {c |}{col 17}{res}{space 2} -.037276{col 29}{space 2} .0327823{col 40}{space 1}   -1.14{col 49}{space 3}0.256{col 57}{space 4}-.1015282{col 70}{space 3} .0269762
{txt}{space 3}pidstrength2 {c |}{col 17}{res}{space 2}-.0255846{col 29}{space 2} .0332876{col 40}{space 1}   -0.77{col 49}{space 3}0.442{col 57}{space 4}-.0908271{col 70}{space 3} .0396579
{txt}{space 2}issueextrem~2 {c |}{col 17}{res}{space 2}  .029935{col 29}{space 2} .0306211{col 40}{space 1}    0.98{col 49}{space 3}0.328{col 57}{space 4}-.0300812{col 70}{space 3} .0899512
{txt}{space 5}interest62 {c |}{col 17}{res}{space 2}  .097695{col 29}{space 2} .0303331{col 40}{space 1}    3.22{col 49}{space 3}0.001{col 57}{space 4} .0382433{col 70}{space 3} .1571467
{txt}{space 5}knowledge2 {c |}{col 17}{res}{space 2} .0360539{col 29}{space 2} .0328582{col 40}{space 1}    1.10{col 49}{space 3}0.273{col 57}{space 4} -.028347{col 70}{space 3} .1004547
{txt}{space 5}education2 {c |}{col 17}{res}{space 2} .0237386{col 29}{space 2} .0331161{col 40}{space 1}    0.72{col 49}{space 3}0.473{col 57}{space 4}-.0411679{col 70}{space 3}  .088645
{txt}{space 11}age2 {c |}{col 17}{res}{space 2} .0083507{col 29}{space 2} .0300528{col 40}{space 1}    0.28{col 49}{space 3}0.781{col 57}{space 4}-.0505516{col 70}{space 3}  .067253
{txt}{space 8}income2 {c |}{col 17}{res}{space 2} .0949809{col 29}{space 2} .0320947{col 40}{space 1}    2.96{col 49}{space 3}0.003{col 57}{space 4} .0320764{col 70}{space 3} .1578854
{txt}{space 9}female {c |}{col 17}{res}{space 2} .0028086{col 29}{space 2} .0296155{col 40}{space 1}    0.09{col 49}{space 3}0.924{col 57}{space 4}-.0552367{col 70}{space 3} .0608538
{txt}{space 10}black {c |}{col 17}{res}{space 2}  .063261{col 29}{space 2} .0300741{col 40}{space 1}    2.10{col 49}{space 3}0.035{col 57}{space 4} .0043168{col 70}{space 3} .1222051
{txt}{space 10}south {c |}{col 17}{res}{space 2}-.0674433{col 29}{space 2} .0290025{col 40}{space 1}   -2.33{col 49}{space 3}0.020{col 57}{space 4}-.1242871{col 70}{space 3}-.0105994
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .0125758{col 29}{space 2} .1740856{col 40}{space 1}    0.07{col 49}{space 3}0.942{col 57}{space 4}-.3286258{col 70}{space 3} .3537774
{space 2}{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}affect92     {col 17}{c |}
{space 7}affect62 {c |}{col 17}{res}{space 2} .6479691{col 29}{space 2} .0202286{col 40}{space 1}   32.03{col 49}{space 3}0.000{col 57}{space 4} .6083218{col 70}{space 3} .6876164
{txt}{space 8}terror6 {c |}{col 17}{res}{space 2} .0288231{col 29}{space 2} .0224464{col 40}{space 1}    1.28{col 49}{space 3}0.199{col 57}{space 4}-.0151709{col 70}{space 3} .0728172
{txt}{space 2}ideostreng~62 {c |}{col 17}{res}{space 2} .0507644{col 29}{space 2} .0241196{col 40}{space 1}    2.10{col 49}{space 3}0.035{col 57}{space 4} .0034909{col 70}{space 3} .0980378
{txt}{space 3}pidstrength2 {c |}{col 17}{res}{space 2} .1631021{col 29}{space 2} .0242214{col 40}{space 1}    6.73{col 49}{space 3}0.000{col 57}{space 4}  .115629{col 70}{space 3} .2105752
{txt}{space 2}issueextrem~2 {c |}{col 17}{res}{space 2} .0562588{col 29}{space 2} .0225144{col 40}{space 1}    2.50{col 49}{space 3}0.012{col 57}{space 4} .0121314{col 70}{space 3} .1003862
{txt}{space 5}interest62 {c |}{col 17}{res}{space 2} .0298418{col 29}{space 2} .0224455{col 40}{space 1}    1.33{col 49}{space 3}0.184{col 57}{space 4}-.0141506{col 70}{space 3} .0738343
{txt}{space 5}knowledge2 {c |}{col 17}{res}{space 2} .0075504{col 29}{space 2} .0242019{col 40}{space 1}    0.31{col 49}{space 3}0.755{col 57}{space 4}-.0398844{col 70}{space 3} .0549852
{txt}{space 5}education2 {c |}{col 17}{res}{space 2}-.0320862{col 29}{space 2}  .024372{col 40}{space 1}   -1.32{col 49}{space 3}0.188{col 57}{space 4}-.0798544{col 70}{space 3}  .015682
{txt}{space 11}age2 {c |}{col 17}{res}{space 2}  -.00989{col 29}{space 2} .0221211{col 40}{space 1}   -0.45{col 49}{space 3}0.655{col 57}{space 4}-.0532465{col 70}{space 3} .0334664
{txt}{space 8}income2 {c |}{col 17}{res}{space 2} .0242684{col 29}{space 2} .0237326{col 40}{space 1}    1.02{col 49}{space 3}0.307{col 57}{space 4}-.0222466{col 70}{space 3} .0707833
{txt}{space 9}female {c |}{col 17}{res}{space 2} .0331458{col 29}{space 2} .0217862{col 40}{space 1}    1.52{col 49}{space 3}0.128{col 57}{space 4}-.0095543{col 70}{space 3} .0758458
{txt}{space 10}black {c |}{col 17}{res}{space 2}-.0108105{col 29}{space 2}   .02219{col 40}{space 1}   -0.49{col 49}{space 3}0.626{col 57}{space 4}-.0543022{col 70}{space 3} .0326811
{txt}{space 10}south {c |}{col 17}{res}{space 2} .0106009{col 29}{space 2} .0214109{col 40}{space 1}    0.50{col 49}{space 3}0.621{col 57}{space 4}-.0313638{col 70}{space 3} .0525655
{txt}{space 10}_cons {c |}{col 17}{res}{space 2}-.2266758{col 29}{space 2} .1268431{col 40}{space 1}   -1.79{col 49}{space 3}0.074{col 57}{space 4}-.4752837{col 70}{space 3} .0219322
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}var(e.terror9){c |}{col 17}{res}{space 2} .7217652{col 29}{space 2} .0237752{col 57}{space 4} .6766392{col 70}{space 3} .7699008
{txt}{space 1}var(e.affect92){c |}{col 17}{res}{space 2}  .391064{col 29}{space 2} .0171294{col 57}{space 4} .3588917{col 70}{space 3} .4261202
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
LR test of model vs. saturated: chi2({res:1})   = {res:     4.10}, Prob > chi2 = {res}0.0429
{txt}
{com}.         
. sem (script9 <- affect62 script6 ideostrength62 pidstrength2 ///
>         issueextremity2 interest62 knowledge2 education2 age2 income2 female ///
>         black south) ///
>         (affect92 <- affect62 script6 ideostrength62 pidstrength2 ///
>         issueextremity2 interest62 knowledge2 education2 age2 income2 female ///
>         black south), standardized              
{res}{txt}(3357 observations with missing values excluded)

Endogenous variables

{p 0 11 2}Observed:{space 2}{res}script9 affect92{p_end}
{txt}
Exogenous variables

{p 0 11 2}Observed:{space 2}{res}affect62 script6 ideostrength62 pidstrength2 issueextremity2 interest62 knowledge2 education2 age2 income2 female black south{p_end}
{txt}
Fitting target model:

Iteration 0:{space 3}log likelihood = {res:-4584.6031}  
Iteration 1:{space 3}log likelihood = {res:-4584.6031}  

{col 1}Structural equation model{col 49}Number of obs{col 67}= {res}       883
{txt}{col 1}Estimation method{col 20}= {res}ml
{txt}{col 1}Log likelihood{col 20}= {res}-4584.6031

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}      OIM
{col 1}   Standardized{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}Structural     {col 17}{txt}{c |}
{space 2}{col 3}script9      {col 17}{c |}
{space 7}affect62 {c |}{col 17}{res}{space 2} .0254587{col 29}{space 2} .0380477{col 40}{space 1}    0.67{col 49}{space 3}0.503{col 57}{space 4}-.0491135{col 70}{space 3} .1000309
{txt}{space 8}script6 {c |}{col 17}{res}{space 2} .2018168{col 29}{space 2} .0321958{col 40}{space 1}    6.27{col 49}{space 3}0.000{col 57}{space 4} .1387142{col 70}{space 3} .2649194
{txt}{space 2}ideostreng~62 {c |}{col 17}{res}{space 2} .0160265{col 29}{space 2}  .037129{col 40}{space 1}    0.43{col 49}{space 3}0.666{col 57}{space 4} -.056745{col 70}{space 3}  .088798
{txt}{space 3}pidstrength2 {c |}{col 17}{res}{space 2}  .077955{col 29}{space 2} .0375137{col 40}{space 1}    2.08{col 49}{space 3}0.038{col 57}{space 4} .0044294{col 70}{space 3} .1514805
{txt}{space 2}issueextrem~2 {c |}{col 17}{res}{space 2}  .073126{col 29}{space 2} .0344353{col 40}{space 1}    2.12{col 49}{space 3}0.034{col 57}{space 4} .0056341{col 70}{space 3}  .140618
{txt}{space 5}interest62 {c |}{col 17}{res}{space 2} .0256331{col 29}{space 2} .0345372{col 40}{space 1}    0.74{col 49}{space 3}0.458{col 57}{space 4}-.0420586{col 70}{space 3} .0933248
{txt}{space 5}knowledge2 {c |}{col 17}{res}{space 2}  .002407{col 29}{space 2} .0371708{col 40}{space 1}    0.06{col 49}{space 3}0.948{col 57}{space 4}-.0704465{col 70}{space 3} .0752605
{txt}{space 5}education2 {c |}{col 17}{res}{space 2}-.0773611{col 29}{space 2} .0373375{col 40}{space 1}   -2.07{col 49}{space 3}0.038{col 57}{space 4}-.1505412{col 70}{space 3} -.004181
{txt}{space 11}age2 {c |}{col 17}{res}{space 2} .0113559{col 29}{space 2} .0340692{col 40}{space 1}    0.33{col 49}{space 3}0.739{col 57}{space 4}-.0554186{col 70}{space 3} .0781304
{txt}{space 8}income2 {c |}{col 17}{res}{space 2} .0641517{col 29}{space 2} .0363601{col 40}{space 1}    1.76{col 49}{space 3}0.078{col 57}{space 4}-.0071127{col 70}{space 3} .1354162
{txt}{space 9}female {c |}{col 17}{res}{space 2} .0027884{col 29}{space 2} .0334758{col 40}{space 1}    0.08{col 49}{space 3}0.934{col 57}{space 4} -.062823{col 70}{space 3} .0683998
{txt}{space 10}black {c |}{col 17}{res}{space 2} .0226643{col 29}{space 2} .0340832{col 40}{space 1}    0.66{col 49}{space 3}0.506{col 57}{space 4}-.0441375{col 70}{space 3}  .089466
{txt}{space 10}south {c |}{col 17}{res}{space 2}-.0270206{col 29}{space 2} .0329489{col 40}{space 1}   -0.82{col 49}{space 3}0.412{col 57}{space 4}-.0915992{col 70}{space 3}  .037558
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .3918598{col 29}{space 2} .1998492{col 40}{space 1}    1.96{col 49}{space 3}0.050{col 57}{space 4} .0001626{col 70}{space 3}  .783557
{space 2}{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}affect92     {col 17}{c |}
{space 7}affect62 {c |}{col 17}{res}{space 2} .6500027{col 29}{space 2} .0196566{col 40}{space 1}   33.07{col 49}{space 3}0.000{col 57}{space 4} .6114766{col 70}{space 3} .6885288
{txt}{space 8}script6 {c |}{col 17}{res}{space 2} .0466019{col 29}{space 2} .0214651{col 40}{space 1}    2.17{col 49}{space 3}0.030{col 57}{space 4} .0045312{col 70}{space 3} .0886727
{txt}{space 2}ideostreng~62 {c |}{col 17}{res}{space 2}  .051738{col 29}{space 2}  .024044{col 40}{space 1}    2.15{col 49}{space 3}0.031{col 57}{space 4} .0046126{col 70}{space 3} .0988635
{txt}{space 3}pidstrength2 {c |}{col 17}{res}{space 2} .1628228{col 29}{space 2}  .024112{col 40}{space 1}    6.75{col 49}{space 3}0.000{col 57}{space 4} .1155641{col 70}{space 3} .2100815
{txt}{space 2}issueextrem~2 {c |}{col 17}{res}{space 2} .0576203{col 29}{space 2} .0223617{col 40}{space 1}    2.58{col 49}{space 3}0.010{col 57}{space 4} .0137922{col 70}{space 3} .1014483
{txt}{space 5}interest62 {c |}{col 17}{res}{space 2} .0279566{col 29}{space 2}   .02239{col 40}{space 1}    1.25{col 49}{space 3}0.212{col 57}{space 4}-.0159269{col 70}{space 3} .0718402
{txt}{space 5}knowledge2 {c |}{col 17}{res}{space 2}  .007998{col 29}{space 2} .0240964{col 40}{space 1}    0.33{col 49}{space 3}0.740{col 57}{space 4}-.0392301{col 70}{space 3}  .055226
{txt}{space 5}education2 {c |}{col 17}{res}{space 2}-.0308935{col 29}{space 2} .0242743{col 40}{space 1}   -1.27{col 49}{space 3}0.203{col 57}{space 4}-.0784702{col 70}{space 3} .0166832
{txt}{space 11}age2 {c |}{col 17}{res}{space 2}-.0111175{col 29}{space 2} .0220867{col 40}{space 1}   -0.50{col 49}{space 3}0.615{col 57}{space 4}-.0544067{col 70}{space 3} .0321717
{txt}{space 8}income2 {c |}{col 17}{res}{space 2} .0242134{col 29}{space 2} .0236211{col 40}{space 1}    1.03{col 49}{space 3}0.305{col 57}{space 4}-.0220831{col 70}{space 3} .0705099
{txt}{space 9}female {c |}{col 17}{res}{space 2} .0308683{col 29}{space 2} .0216902{col 40}{space 1}    1.42{col 49}{space 3}0.155{col 57}{space 4}-.0116436{col 70}{space 3} .0733802
{txt}{space 10}black {c |}{col 17}{res}{space 2}-.0097595{col 29}{space 2} .0221017{col 40}{space 1}   -0.44{col 49}{space 3}0.659{col 57}{space 4}-.0530781{col 70}{space 3}  .033559
{txt}{space 10}south {c |}{col 17}{res}{space 2} .0089696{col 29}{space 2}   .02137{col 40}{space 1}    0.42{col 49}{space 3}0.675{col 57}{space 4}-.0329149{col 70}{space 3} .0508541
{txt}{space 10}_cons {c |}{col 17}{res}{space 2}-.2493734{col 29}{space 2} .1270141{col 40}{space 1}   -1.96{col 49}{space 3}0.050{col 57}{space 4}-.4983165{col 70}{space 3}-.0004303
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}var(e.script9){c |}{col 17}{res}{space 2} .9259331{col 29}{space 2} .0166436{col 57}{space 4} .8938802{col 70}{space 3} .9591354
{txt}{space 1}var(e.affect92){c |}{col 17}{res}{space 2} .3891358{col 29}{space 2} .0170601{col 57}{space 4}  .357095{col 70}{space 3} .4240516
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
LR test of model vs. saturated: chi2({res:1})   = {res:     3.37}, Prob > chi2 = {res}0.0665
{txt}
{com}.         
. sem (citizen9 <- affect62 citizen6 ideostrength62 pidstrength2 ///
>         issueextremity2 interest62 knowledge2 education2 age2 income2 female ///
>         black south) ///
>         (affect92 <- affect62 citizen6 ideostrength62 pidstrength2 ///
>         issueextremity2 interest62 knowledge2 education2 age2 income2 female ///
>         black south), standardized              
{res}{txt}(3358 observations with missing values excluded)

Endogenous variables

{p 0 11 2}Observed:{space 2}{res}citizen9 affect92{p_end}
{txt}
Exogenous variables

{p 0 11 2}Observed:{space 2}{res}affect62 citizen6 ideostrength62 pidstrength2 issueextremity2 interest62 knowledge2 education2 age2 income2 female black south{p_end}
{txt}
Fitting target model:

Iteration 0:{space 3}log likelihood = {res:-4349.1505}  
Iteration 1:{space 3}log likelihood = {res:-4349.1505}  

{col 1}Structural equation model{col 49}Number of obs{col 67}= {res}       882
{txt}{col 1}Estimation method{col 20}= {res}ml
{txt}{col 1}Log likelihood{col 20}= {res}-4349.1505

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}      OIM
{col 1}   Standardized{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}Structural     {col 17}{txt}{c |}
{space 2}{col 3}citizen9     {col 17}{c |}
{space 7}affect62 {c |}{col 17}{res}{space 2}  .119427{col 29}{space 2} .0362862{col 40}{space 1}    3.29{col 49}{space 3}0.001{col 57}{space 4} .0483073{col 70}{space 3} .1905466
{txt}{space 7}citizen6 {c |}{col 17}{res}{space 2} .3017309{col 29}{space 2} .0296404{col 40}{space 1}   10.18{col 49}{space 3}0.000{col 57}{space 4} .2436368{col 70}{space 3}  .359825
{txt}{space 2}ideostreng~62 {c |}{col 17}{res}{space 2} .0311128{col 29}{space 2} .0356308{col 40}{space 1}    0.87{col 49}{space 3}0.383{col 57}{space 4}-.0387223{col 70}{space 3} .1009479
{txt}{space 3}pidstrength2 {c |}{col 17}{res}{space 2}-.0250393{col 29}{space 2} .0360969{col 40}{space 1}   -0.69{col 49}{space 3}0.488{col 57}{space 4}-.0957879{col 70}{space 3} .0457092
{txt}{space 2}issueextrem~2 {c |}{col 17}{res}{space 2} .0460007{col 29}{space 2} .0332843{col 40}{space 1}    1.38{col 49}{space 3}0.167{col 57}{space 4}-.0192354{col 70}{space 3} .1112367
{txt}{space 5}interest62 {c |}{col 17}{res}{space 2}  .058104{col 29}{space 2} .0330055{col 40}{space 1}    1.76{col 49}{space 3}0.078{col 57}{space 4}-.0065855{col 70}{space 3} .1227936
{txt}{space 5}knowledge2 {c |}{col 17}{res}{space 2} .0153464{col 29}{space 2} .0355404{col 40}{space 1}    0.43{col 49}{space 3}0.666{col 57}{space 4}-.0543116{col 70}{space 3} .0850043
{txt}{space 5}education2 {c |}{col 17}{res}{space 2}-.0086279{col 29}{space 2} .0358004{col 40}{space 1}   -0.24{col 49}{space 3}0.810{col 57}{space 4}-.0787954{col 70}{space 3} .0615395
{txt}{space 11}age2 {c |}{col 17}{res}{space 2}-.0136605{col 29}{space 2} .0326662{col 40}{space 1}   -0.42{col 49}{space 3}0.676{col 57}{space 4}-.0776851{col 70}{space 3} .0503641
{txt}{space 8}income2 {c |}{col 17}{res}{space 2}-.0038801{col 29}{space 2} .0349094{col 40}{space 1}   -0.11{col 49}{space 3}0.911{col 57}{space 4}-.0723012{col 70}{space 3}  .064541
{txt}{space 9}female {c |}{col 17}{res}{space 2} .0430176{col 29}{space 2} .0320603{col 40}{space 1}    1.34{col 49}{space 3}0.180{col 57}{space 4}-.0198194{col 70}{space 3} .1058546
{txt}{space 10}black {c |}{col 17}{res}{space 2} .0773081{col 29}{space 2} .0325744{col 40}{space 1}    2.37{col 49}{space 3}0.018{col 57}{space 4} .0134634{col 70}{space 3} .1411528
{txt}{space 10}south {c |}{col 17}{res}{space 2} .0142138{col 29}{space 2} .0315894{col 40}{space 1}    0.45{col 49}{space 3}0.653{col 57}{space 4}-.0477003{col 70}{space 3}  .076128
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .2170833{col 29}{space 2} .1902642{col 40}{space 1}    1.14{col 49}{space 3}0.254{col 57}{space 4}-.1558278{col 70}{space 3} .5899944
{space 2}{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}affect92     {col 17}{c |}
{space 7}affect62 {c |}{col 17}{res}{space 2} .6524734{col 29}{space 2} .0197407{col 40}{space 1}   33.05{col 49}{space 3}0.000{col 57}{space 4} .6137824{col 70}{space 3} .6911644
{txt}{space 7}citizen6 {c |}{col 17}{res}{space 2} .0156953{col 29}{space 2} .0215095{col 40}{space 1}    0.73{col 49}{space 3}0.466{col 57}{space 4}-.0264625{col 70}{space 3} .0578531
{txt}{space 2}ideostreng~62 {c |}{col 17}{res}{space 2} .0497621{col 29}{space 2} .0241798{col 40}{space 1}    2.06{col 49}{space 3}0.040{col 57}{space 4} .0023707{col 70}{space 3} .0971536
{txt}{space 3}pidstrength2 {c |}{col 17}{res}{space 2} .1644483{col 29}{space 2} .0242238{col 40}{space 1}    6.79{col 49}{space 3}0.000{col 57}{space 4} .1169706{col 70}{space 3}  .211926
{txt}{space 2}issueextrem~2 {c |}{col 17}{res}{space 2}  .057616{col 29}{space 2} .0225916{col 40}{space 1}    2.55{col 49}{space 3}0.011{col 57}{space 4} .0133374{col 70}{space 3} .1018947
{txt}{space 5}interest62 {c |}{col 17}{res}{space 2} .0314238{col 29}{space 2} .0224476{col 40}{space 1}    1.40{col 49}{space 3}0.162{col 57}{space 4}-.0125727{col 70}{space 3} .0754203
{txt}{space 5}knowledge2 {c |}{col 17}{res}{space 2} .0098946{col 29}{space 2} .0241349{col 40}{space 1}    0.41{col 49}{space 3}0.682{col 57}{space 4} -.037409{col 70}{space 3} .0571982
{txt}{space 5}education2 {c |}{col 17}{res}{space 2} -.033438{col 29}{space 2} .0242982{col 40}{space 1}   -1.38{col 49}{space 3}0.169{col 57}{space 4}-.0810616{col 70}{space 3} .0141856
{txt}{space 11}age2 {c |}{col 17}{res}{space 2}-.0084237{col 29}{space 2} .0221831{col 40}{space 1}   -0.38{col 49}{space 3}0.704{col 57}{space 4}-.0519017{col 70}{space 3} .0350543
{txt}{space 8}income2 {c |}{col 17}{res}{space 2}  .025292{col 29}{space 2} .0236974{col 40}{space 1}    1.07{col 49}{space 3}0.286{col 57}{space 4}-.0211542{col 70}{space 3} .0717381
{txt}{space 9}female {c |}{col 17}{res}{space 2} .0314278{col 29}{space 2} .0217847{col 40}{space 1}    1.44{col 49}{space 3}0.149{col 57}{space 4}-.0112694{col 70}{space 3}  .074125
{txt}{space 10}black {c |}{col 17}{res}{space 2}-.0100353{col 29}{space 2} .0222032{col 40}{space 1}   -0.45{col 49}{space 3}0.651{col 57}{space 4}-.0535528{col 70}{space 3} .0334822
{txt}{space 10}south {c |}{col 17}{res}{space 2} .0096312{col 29}{space 2} .0214519{col 40}{space 1}    0.45{col 49}{space 3}0.653{col 57}{space 4}-.0324139{col 70}{space 3} .0516762
{txt}{space 10}_cons {c |}{col 17}{res}{space 2}-.2273569{col 29}{space 2} .1273102{col 40}{space 1}   -1.79{col 49}{space 3}0.074{col 57}{space 4}-.4768803{col 70}{space 3} .0221666
{txt}{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}var(e.citizen9){c |}{col 17}{res}{space 2} .8506633{col 29}{space 2} .0212954{col 57}{space 4} .8099325{col 70}{space 3} .8934424
{txt}{space 1}var(e.affect92){c |}{col 17}{res}{space 2} .3922227{col 29}{space 2} .0171807{col 57}{space 4} .3599542{col 70}{space 3} .4273839
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
LR test of model vs. saturated: chi2({res:1})   = {res:     8.12}, Prob > chi2 = {res}0.0044
{txt}
{com}.                 
.         
.         
. 
{txt}end of do-file

{com}. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}/Users/adamenders/Dropbox/Perceived vs. Affective Polarization/Data and Code/Supplemental Analysis, Stata log.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res} 9 Mar 2020, 13:49:16
{txt}{.-}
{smcl}
{txt}{sf}{ul off}